a level computer science coursework

All about A level Computer Science – course information

What's a level computer science about.

A level Computer science is split into two complementary sections, programming and theory.  On the programming side of the course, students can learn a programming language (chosen by your teachers from C#, Java, Pascal/Delphi, Python and VB.Net).  You will cover  the fundamentals of programming, data structures, algorithms, and object-orientated programme design.

The theory side of computer science teaches about the internal workings of a computer, right down the basics of how all data is stored using binary, whether that data consists of numbers, text, pictures or even music.  It goes on from there to cover aspects of computer architecture, showing exactly how data is accessed from main memory using assembly language instructions and the fetch-execute cycle.

As well as covering programming the course aims to promote good programming practices such as avoiding global variables, sensible variable naming, structured programming, good re-use of code through procedures and functions, and proper commenting of code.  It also covers higher level concepts such as the social and legal impact of computers, and how to go about breaking down a big problem into individual programmable steps.

W hat sort of work is involved?

The A level Computer science course consists of work towards two exam papers, both worth 40% of the whole, plus non-exam assessment worth 20% which will typically be done over a period of about 3 months.

The first exam is a programming test, which some exam boards, such as the AQA ,  like to do using an on-screen exam.  This will test your ability to solve problems as much as it will test your technical knowledge of the programming language you have learned.

The second exam tests theory and is a written exam.  Questions are designed to test your knowledge of computer systems, how they are formed, the social and legal parts of computing, communication, networking and databases.

For the non-exam assessment you  pick your own project which must have a significant programming element.  You will create a program to solve a problem, such as writing a computer game, making a mobile phone application or doing an investigation into machine learning.  There is no restriction on programming language used in the project, so you could use Swift, Objective C, C++ or any other language you wanted to do your project.  However,  drag-and-drop languages, such as Scratch, are not allowed. When writing coursework you won’t just be expected to produce working code, but will be expected to write good, well structured working code.

What background do I need?

To do A level Computer science it is not essential to have done computer science at GCSE, though it is advisable to have done some practice of programming in your own time.  The course has a significant programming element and those who have no previous experience of programming often find it very challenging.

You ought to have at least a B-grade in mathematics.  There are several topics that require the ability to reason logically and apply mathematical and logical processes to solutions.  It is likely that if you find mathematics enjoyable and interesting then you will also like computer science.

Where can it lead?

A level Computer science is naturally a strong subject to take if you wish to go on to do computer science at degree level, and although most computing-based degree courses don't require Computer science A level there are a number of software engineering courses which do.  There are also other degree courses such as information technology and information systems which will be served well by a Computer science A level.

After university, there are numerous interesting fields of study and professions that you can go in to.  Computer science will lead on to robotics, artificial intelligence, machine learning, cloud computing, big data processing, networking, ethical hacking, computer game development, home automation or even teaching.  So much of the world uses computers nowadays that having a good understanding of how computers work and how to program them will set you up for success in many strands of life.

Numbers of computers are also increasing in many developing countries too, meaning that your skills in computer science will be very portable.  The most popular programming languages in the world are based on the English language using statements such as for, while, if, else, repeat , so studying computer science in an English speaking college will give you a good foundation if you wish to travel and find a job working with computers in another country.

One year course?

Due to the coursework element, A level Computer science is very difficult to do in one year.  To succeed you would need to already have a firm grasp of programming such that you could begin the year doing coursework and getting it out of the way, leaving you enough time to cover the theory before taking exams in June.

There is an AS-level available which covers most of the topics but not in as much detail as the A-level.  Like the A level, there are two exams, one of which is programming and the other theory but they are each worth 50% of your overall grade.

As previously mentioned, A level Computer science consists of two exam papers, each 2 1/2 hours long and each worth 40%. The remaining 20% comes from your coursework.

The coursework assesses your ability to take on a significant problem and produce a solution to it.  Despite the large programming element, you will actually be marked on the documentation you produce.  This will typically consist of an analysis, designing the solution, annotated code showing your finished solution, tests demonstrating that your solution works and an evaluation.

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A-level Computer Science

Computer Science has rational thinking at its core; combining human and computer intelligence to provide intelligent solutions to problems. Choosing to study International A-level Computer Science can open doors to various career opportunities in data science, web development, product management and software development, or prepare you for higher education at university .

In this engaging online computer science course, you’ll study communication and Internet technologies, software development, artificial intelligence, data representation and much more. As you study, you’ll develop key skills such as abstraction, decomposition and algorithmic thinking.

What you will learn

Unit 1 - information representation.

• Binary Number System
• Binary Coded Decimal
• Hexadecimal 
• Bits, Bytes and Binary
• Representing Images
• Analogue and Digital Sound
• Data Compression

Unit 2 - Communication and Internet Technologies

• Data Transmission
• Wireless Networking, CSMA and SSID
• Structure of the Internet
• Packet Switching and Routers
• IP Addresses 
• Network Topology
• Client-Server and Peer-to-Peer
• Client Server Model

Unit 3 - Hardware

• Computers and their components
• Logic gates
• Creating logic circuits
• Interpreting the results of a truth table

Unit 4 - Processor Fundamentals

• Central Processing Unit
• The Fetch-Decode-Execute Cycle
• The Processor
• Assembly Language
• Machine Code
• Bit Manipulation

Unit 5 - System Software

• Operating systems (OS)
• Processor scheduling
• Programming language classification
• Language translators
• Machine code

Unit 6 - Security, Privacy and Data Integrity

• Data security
• Cyber security
• MALWARE – malicious software
• Data integrity

Unit 7 - Ethics and Ownership

• Ethics and ownership
• The rise of artificial intelligence
• The Computer Misuse Act 1990
• Data Protection Act (1998)
• Copyright, Designs and Patents Act (1998)
• Introduction to software licences

Unit 8 - Databases

• Flat file databases
• Relational database model
• Database normalisation
• Database Management Systems (DBMS)
• Data Definition Language (DDL) and Data Manipulation Language (DML)
• Common data types
• Linking tables

Unit 9 - Fundamental Problem Solving - Algorithm Design and Problem Solving

• Abstraction and decomposition
• Solving logic problems
• Software development

Unit 10 - Fundamental Problem Solving - Data Types and Structures

• Data Types and Records
• Searching and sorting algorithms
• Files and Exception Handling
• Abstract Data Types (ADT)

Unit 11 - Fundamental Problem Solving - Programming

• Complex Boolean Expressions
• The CASE Statement
• Subroutines

Unit 12 - Fundamental Problem Solving - Software Development

• Program Development Life Cycle
• The Waterfall Model
• Iterative and Rapid Application Development
• Program Design
• Program Testing and Maintenance
• Error Types

Unit 13 - Advanced Theory - Data Representation

• User Defined Data Types
• File Organisation and Access
• Floating-Point Numbers, Representation and Manipulation
• Precision and Normalisation

Unit 14 - Advanced Theory - Communication and Internet Technologies

• the TCP/IP Model
• Circuit Switching 
• Packet Switching

Unit 15 - Advanced Theory - Hardware and Virtual Machines

• Processors, Parallel Processing and Virtual Machines
• Comparing RISC and CISC
• Virtual Machines
• Boolean Algebra and Logic Gates
• De Morgan’s Laws
• Karnaugh Maps

Unit 16 - Advanced Theory - System Software

• Purposes of an Operating System
• Processor Scheduling
• IO Device Management
• Translation Software
• Backus-Naur Form
• Syntax Diagram

Unit 17 - Advanced Theory - Security

• Encryption Protocols and Digital Certificates
• Types of Encryption
• Encryption Protocol
• The Electronic Communications Act (2000)
• Digital Certificates
• Digital Signatures

Unit 18 - Advanced Theory - Artificial Intelligence

• Machine Learning
• Deep Learning
• Reinforcement Learning
• Dijkstra’s Algorithm
• A* Algorithm

Unit 19 - Computational Thinking and Problem Solving

• Abstract Data Types
• Linked Lists
• Binary Tree
• Big O Notation

Unit 20 - Further Programming

• Programming Paradigms
• Imperative (High Level) Programming
• Files Processing and Exception Handling
• Inputs and Outputs
• Exception Handling

Awarding Body

Cambridge Assessment International Education (CAIE) is the world’s largest provider of  A-level courses  and  GCSE courses , qualifications and exams, delivering assessments to over 8 million learners in over 170 countries.

Recognised through UCAS

This course carries UCAS points . This means that it can be used to gain direct access to University courses and other Higher Education, through the UCAS system .

Course Outcome

After completing the course, you will be awarded the qualification: A-level Computer Science, issued by  CAIE  (Cambridge Assessment International Education. This syllabus ( 9618 ) has been selected specifically because it is best suited to distance learning. Your certificate will be identical to that issued in any other school, college or university.

How is this course assessed or examined?

You will be expected to complete three standard A-level Computer Science written exams and one practical exam:

Written exams:

• Paper 1:  1 hour 30 minutes, 25% of A-level, 75 marks.
• Paper 2:  1 hour 30 minutes, 25% of A-level, 75 marks.
• Paper 3:  2 hours 30 minutes, 25% of A-level, 75 marks.

Practical exam:

•  2 hours 30 minutes, 25% of A-level, 75 marks.

As part of the practical exam, you will submit complete program code and evidence of testing and will be required to use either Java, VB.NET or Python programming languages.

Entry requirements

In order to study this course, you will need to have achieved a  maths GCSE  or the equivalent. If you wish to study computer science at a degree level, then you’ll need to combine this qualification with  A-level maths , as this is a requirement at many universities. It is a difficulty level three: the equivalent difficulty of an A-level or BTEC, usually suitable for most learners of all ages.

Past Papers

You can access past papers for this course . They are free to access and cover a range of exam boards.

Find out more about the exams here .

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Cambridge International AS & A Level Computer Science

Topic outline.

• Please rotate your device.

• Syllabus content - what you need to know about

There are four components that you will need to take:

• Paper 1 (Theory Fundamentals)

Paper 2 (Fundamental Problem-solving and Programming Skills)

• Paper 3 (Advanced theory)
• Paper 4 (Practical)

Key concepts

Key concepts are essential ideas that help you to develop a deep understanding of your subject and make links between different aspects of the course. The key concepts for Cambridge International AS & A Level Computer Science are:

• Computational thinking

Computational thinking is a set of fundamental skills that help produce a solution to a problem. Skills such as abstraction, decomposition and algorithmic thinking are used to study a problem and design a solution that can be implemented. This may involve using a range of technologies and programming languages.

• Programming paradigms

A programming paradigm is a way of thinking about or approaching problems. There are many different programming styles that can be used, which are suited to unique functions, tools and specific situations. An understanding of programming paradigms is essential to ensure they are used appropriately, when designing and building programs.

• C ommunication

Communication is a core requirement of computer systems. It includes the ability to transfer data from one device or component to another and an understanding of the rules and methods that are used in this data transfer. Communication could range from the internal transfer of data within a computer system, to the transfer of a video across the internet.

• Comput er architecture and hardware 

Computer architecture is the design of the internal operation of a computer system. It includes the rules that dictate how components and data are organised, how data are communicated between components, to allow hardware to function. There is a range of architectures, with different components and rules, that are appropriate for different scenarios.

All computers comprise of a combination of hardware components, ranging from internal components, such as the Central Processing Unit (CPU) and main memory, to peripherals. To produce effective and efficient programs to run on hardware, it is important to understand how the components work independently and together to produce a system that can be used. Hardware needs software to be able to perform a task. Software allows hardware to become functional. This enables the user to communicate with the hardware to perform tasks.

• Data representation and structures  

Computers use binary and understanding how a binary number can be interpreted in many different ways is important. Programming requires an understanding of how data can be organised for efficient access and/or transfer. 

These key concepts help you to gain:

• a greater depth as well as breadth of subject knowledge 

• confidence, especially in applying your knowledge and skills in new situations

• the vocabulary to discuss the subject conceptually and show how different aspects link together

• a level of mastery of their subject to help them enter higher education. 

Make sure you always check the latest syllabus, which is available at  www.cambridgeinternational.org .

• How you will be assessed
• Please rotate your device
• What skills will be assessed?
• The examiners take account of the following skills areas (assessment objectives) in the examinations: AO1: Knowledge with understanding Demonstrate knowledge and understanding of the principles and concepts of computer science including abstraction, logic, algorithms and data representation. AO2: Application Apply knowledge and understanding of the principles and concepts of computer science, including to analyse problems in computational terms. AO3: Design, program and evaluation Design, program and evaluate computer systems to solve problems, making reasoned judgements about these.
• Command words
• The flipcards below include command words used in the assessment for this syllabus. The use of the command word will relate to the subject context.
• Example candidate response
• All information and advice in this section is specific to the example question and response being demonstrated. It should give you an idea of how your responses might be viewed by an examiner but it is not a list of what to do in all questions. In your own examination, you will need to pay careful attention to what each question is asking you to do.

Example candidate response and examiner comments

• (a) Application layer Transport (layer) Internet (layer) Network (access layer) [See examiner comment] (b) (i) Peer – to – peer. (ii) File sharing. (iii) BitTorrent client software is made available, this is used to load the torrent descriptor for the required file by computers joining it swarm. A server, called tracker, keeps records of all the computers joining the swarm and allows them to connect to each other by sharing their IP addresses. The torrent is split into small pieces that can be downloaded or uploaded by each computer in the swarm. Once a computer has downloaded a piece of the torrent file it can upload that piece to other computers in the swarm and become a seed. (c) Protocol 1 SMTP Example Sending email messages Protocol POP3 Example retirement of email messages [See examiner comment] [Total mark awarded]
• Explore the advice below to help you revise and prepare for the examinations.  It is divided into general advice for all papers and more specific advice for each of the papers.
• Find out when the examinations are and plan your revision so you have enough time for each topic. A revision timetable will help you
• Find out how long each paper is and how many questions you have to answer
• Know the meaning of the command words used in questions and how to apply them to the information given. Highlight the command words in past papers and check what they mean. There is a list on page 11 of this guide
• Make revision notes; try different styles of notes. See the Learner Guide: Planning, Reflection and Revision  which as ideas about note-taking. Discover what works best for you
• Work for short periods then have a break. Revise small sections of the syllabus at a time
• Build your confidence by practising questions on each of the topics
• Make sure you practice lots of past examination questions so that you are familiar with the format of the examination papers. You could time yourself when doing a paper so that you know how quickly you need to work in the real examination
• Look at mark schemes to help you understand how the marks are awarded for each question
• Make sure you are familar with the technical terminology that you need for this syllabus. Your teacher will be able to advise you on what is expected.
• Read the instructions carefully and answer all the questions
• Check the number of marks for each question or part question. This helps you to judge how long you should be spending on the response. You don't want to spend too long on some questions and then run out of time at the end
• Do not leave out questions or parts of questions. Remember, no answer means no mark
• If a question has several parts, then the parts with more marks will need more time and more developed answers
• You do not have to answer the questions in the order they are printed in the answer booklet. You may be able to do a later question more easily then come back to an earlier one for another try
• Identify the command words – you could underline or highlight them
• Identify the technical terms and perhaps underline them too
• Try to put the question into your own words to understand what it is really asking.
• Read all parts of a question before starting your answer. Think carefully about what is needed for each part. You will not need to repeat material
• Use your knowledge and understanding
• Do not write everything you know about a topic. Only use the information you need to answer the question.
• Make sure that you have answered everything that a question asks. Sometimes one part requires two things, e.g. 'Calculate...' and 'Show your working.'. It is easy to concentrate on the first request and forget about the second one
• Always show your working. Marks are usually awarded for using correct steps in the method even if you make a mistake somewhere
• Don't cross out any working in a calculation until you have replaced it by trying again. Even if you know it's not correct you may still be able to get method marks. If you have made more than two attempts, make sure you cross out all except the one you want marked
• Make sure all your numbers are clear, for example make sure your '1' doesn't look like a '7'
• If you need to change a word or a number, it is better to cross out your work and rewrite it. Don't try to write over the top of your previous work as it will be difficult to read and you may not get the marks
• Don't write any pseudocode answers in two columns in the examination. It is difficult for the examiners to read and follow your working.
• Always use the logic gate symbols from the syllabus when drawing logic circuits
• Always use the opcodes given on the syllabus or shown on the examination paper when writing assembly language instructions
• Try and use capital letters when writing assembly language opcodes, SQL, or pseudocode commands so they can be clearly recognised as commands by the examiner
• Where possible use SQL and pseudocode commands that are given in the syllabus, any other commands should be identified and explained.
• Try and use capital letters when writing pseudocode commands so they can be clearly recognised as commands by the examiner
• Where possible use pseudocode commands that are given in the syllabus, any other commands should be identified and explained
• Annotate pseudocode with comments
• Fully label diagrams.
• Remember you will need to write and test programs in the examination

Visual Basic

• Be able to use your chosen programming language in console mode
• Get plenty of practice at debugging and testing programs using your chosen programming language
• Where possible use the same programming language for all your answers.

• Paper 1 - Theory Fundamentals
• 1.1 Data Representation 1.2 Multimedia 1.3 Compression 1.4 Communication 1.5 Hardware 1.6 Processor Fundamentals 1.7 System Software 1.8 Security, privacy and data integrity 1.9 Ethics and ownership 1.10 Databases TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT
• Paper 2 - Fundamental Problem-solving and Programming Skills
• 2.1 Computational thinking skills 2.2 Algorithm Design 2.3 Data types and structures 2.4 Programming 2.5 Software Development TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT
• Paper 3 - Advanced Theory
• 3.1 Data Representation 3.2 Communication and internet technologies 3.3 Hardware 3.4 System Software 3.5 Security 3.6 Artificial Intelligence (AI) 3.7 Algorithms TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT
• Paper 4 - Practical
• 4.1 Programming
• Useful websites
• The websites listed below are reliable useful resources to help you study for your Cambridge International AS and A Level Computer Science.

www.w3schools.com/

www.jetbrains.com/idea/documentation/

www.jetbrains.com/idea/download/#section=windows -

https://visualstudio.microsoft.com/vs/express/

www.python.org/downloads/

Prolog 

www.swi-prolog.org/

British Computer Society Glossary

www.bcs.org/category/5656

CIE A Level Computer Science

Unit 1 – information representation, 1.1 data representation.

• Binary & Denary Number Systems
• Hexadecimal Number Systems
• Binary and Decimal Prefixes
• One’s Compliment and Two’s Compliment
• Binary Addition and Subtraction
• Binary Coded Decimal
• ASCII, Extended ASCII and Unicode
• Binary Addition

1.2 Multimedia – Graphics, Sound

• Bitmap Images
• Vector Images
• Bitmaps vs Vectors
• Encoding & Compressing Video
• Encoding Sound

1.3 Compression

• The need for compression
• Lossy vs Lossless Compression
• Compression algorithms

Unit 2 – Communication

2.1 networks including the internet.

• Purpose of networking of devices
• Client-Server vs Peer to Peer
• Thin and Thick Clients
• Network Topologies
• Cloud Computing
• Wired and Wireless Networks
• Network Hardware
• Network routing and collisions(CSMA/CD)
• Bit Streaming
• WWW and the Internet
• Internet Hardware
• IPv4 & IPv6 Addresses
• Subnets & Network Masks
• Public vs Private IP Addresses
• Static Vs Dynamic IP, DHCP
• URLs, DNS and Serving Web Pages
• Client Side & Server Side Scripting

Unit 2 Past Paper Questions

Unit 3 – Hardware

3.1 computers and their components.

• Input Devices
• Laser Printer
• Primary Storage
• Secondary Storage Devices
• Embedded Systems
• Virtual and Augmented Reality
• RAM and ROM
• SRAM vs DRAM
• ROM,PROM,EPROM,EEPROM
• Open & Closed Loop Systems

CIE Teacher Support Materials Input/Output Devices

3.2 Logic Gates and Logic Circuits

• Logic Gates
• Logic Circuits
• Truth Tables

Unit 4 – Processor Fundamentals

4.1 central processing unit (cpu) architecture.

• VON Neumann Architecture
• Motherboard Ports
• Fetch  – Execute Cycle
• Register Transfer Notation
• ALU,CU,IAS, System Clock
• CPU Performance Factors

4.2 Assembly Language

• Assembly Language Vs Machine Code & The assembly process
• Grouping Instruction Sets
• Modes of addressing
• Dynamic Link Libraries

4.3 Bit manipulation

• Binary Shifts
• Bit Manipulation & Bitwise Operations

Unit 5 – System Software

5.1 operating systems.

• Purpose of an Operating System
• Operating System User Interface Types
• Management tasks
• Utility Software
• Program Libraries

5.2 Language Translators

• Assembler Software
• Interpreters

Unit 6 – Security, privacy and data integrity

6.1 data security.

• Security, Privacy and Integrity
• Data and System Security
• Computer & Network Threats
• Security / Threat reduction measures
• Backing Up Data

6.2 Data Integrity

• Methods of data validation
• Methods of data verification

Unit 6 Past Paper Questions

Unit 7 – Ethics and Ownership

7.1 ethics and ownership.

• Copyright legislation
• Software Licences
• Ethical implications of artificial intelligence
• IEEE Code of Ethics Rules
• IEEE/ACM Software Engineering Guiding Principles

CIE Ethics Teacher Materials

Unit 8 – Databases

8.1 database concepts.

• Introduction to Relational Databases
• Entity relationship diagrams
• Referential Integrity
• Normalisation process  – First, Second, Third Normal Form

8.2 Database Management System (DBMS)

• Features of a database management system & Query Processor
• DBMS Software Tools
• Backup Procedures
• Online,Offline, Onsite,Offsite Backups

8.3 Data Definition Language (DDL) and Data Manipulation Language (DML)

• Role of Data Definition Language
• Role of Data Manipulation Language
• SQL Language
• SQL DDL Queries
• SQL DML Queries

Helpful Resources

• Databases Past Paper Questions
• SQL Practice Games
• SQLite3 Cheat Sheet

Unit  9 – Algorithm Design and Problem-Solving

9.1 computational thinking skills.

• Input, process, Output
• Abstraction
• Decomposition
• Abstraction & Decomposition
• Step-wise refinement

9.2 Algorithms

• Identifier names and tables
• Logic statements

Unit 10 – Data Types and structures

10.1 data types and records.

• Selection of data types
• User Defined Types (Record, Enumerator, Set)

10.2 Arrays

• 1 Dimensional Arrays
• 2 Dimensional Arrays

Search Algorithms

• Linear Search
• Binary Search

Sorting Algorithms

• Bubble Sort
• Insertion Sort
• Lower and Upper Bounds
• Reading/Writing Text Files
• Reading/Writing CSV Files

10.4 Introduction to Abstract Data Types (ADT)

• Introduction to abstract data types
• Linked List

Unit 11 – Programming

11.1 programming basics.

• Basic input, processing & output
• Conditionals
• Dictionaries
• Subroutines

CIE Pseudocode

• Introduction, Input, Output, Variables
• If & Case Statements
• File Handling
• Functions & Procedures

Abstract Data Types

(Also create a cheat sheet and add it here)

11.2 Constructs

• Programming Constructs

11.3 Structured Programming

• Functions Exercises
• Input Parameters
• Efficient code

Unit 12 – Software Development

12.1 program development life cycle.

• Development life cycles
• Waterfall model
• Rapid Application Development

12.2 Program Design

• Structure Charts
• State Transition Diagrams

13. Program Testing & Maintenance

• Integrated Development Environments
• Syntax, Runtime & Logical Errors
• Methods of Testing
• Choosing Test Data
• Program Maintenance

Unit 13 – Data Representation (A – level)

13.1 user defined types.

• Classes, Objects & Instances

13.2 File Organisation & Access

• File organisation and access
• Hash Tables & Hashing Functions

13.3 Floating-point numbers, representation and manipulation

Unit 14  – Communication & Internet Technologies

14.1 protocols.

• The need for protocols
• Protocol stack
• TCP/IP Protocol Suite
• HTTP,FTP,POP3,IMAP,SMTP,BitTorrent

14.2 Circuit switching, packet switching

• Circuit Switching
• Packet Switching
• Function of a router

Unit 15 – Hardware & Virtual Machines

15.1 processors, parallel processing and virtual machines.

• RISC & CISC Computers
• Interrupt Handling in RISC & CISC
• Pipelining & Registers
• SISD,SIMD,MISD,MIMD
• Massively Parallel Computers
• Virtual Machines

15.2 Boolean Algebra and Logic Circuits

• Half Adders & Full Adders
• Flip Flop Circuits
• Karnaugh Maps
• Boolean Algebra Simplification Examples

Unit 16 – System Software

16.1 purposes of an operating system (os).

Process Management

16.2 Translation Software

• Compilers and compilation stages
• Syntax Diagrams
• Backus-Naur Form
• Reverse Polish Notation

Unit 17 – Security

17.1 encryption, encryption protocols and digital certificates.

• Symmetric Encryption
• Asymmetric Encryption
• Digital Certificates
• Transport Layer Security & Digital Certificates (SSL/TLS)
• Quantum Cryptography

Unit 18 – Artificial Intelligence

18.1 artificial intelligence.

• Artificial Intelligence, Machine Learning and Deep Learning
• Classification, Regression, Clustering & Reinforcement  &
• Dijkstra’s Algorithm
• A* Algorithm
• Deep Learning & Neural Networks
• Supervised, Unsupervised Learning & Reinforcement Learning
• Back Propagation

Artificial Intelligence Exam Questions

Unit 19 – Computational thinking and problem solving

19.1 algorithms.

Big O Notation with searching and sorting algorithms

• Binary Tree

19.2 Recursion

• Maze Solving Recursive Algorithm

Unit 20 – Further Programming

20.1 programming paradigms.

• Low Level Programming
• Imperative (Procedural) Programming
• Object Orientated Programming
• Declarative Programming

20.2 File Processing and Exception Handling

June 2021-2023 9618 Syllabus

Folder Structure

Pseudocode Guide

AS & A Level Exam Components

Paper 1 -Theory Fundamentals

• Sections 1 to 8
• 90 minute exam (25% of A level)

Paper 2 – Problem-solving and  Programming

• Sections  9 to 12
• 120 minute exam (25% of A level)
• Includes writing algorithms in code *, Pseudocode & Flowcharts

Paper 3 – Advanced Theory

• Sections 13 to 20
• 90 minute exam (25% of A level)

Paper 4 – Practical

• Sections 19 to 20
• 150 minute exam (25% of A level)
• Answered on computer
• Students will submit program code* and evidence of testing
• No email or internet access

* Permitted Programming languages – Java, VB.net or Python.  No other languages are allowed.

Exam Practice

Past papers, mark schemes & specimen papers.

Past Papers & Mark Schemes

Specimen Papers 2021+

Printable revision resources

Paper 4 Practice Tasks

Paper 4 Programming Skills CheckList

Year 11 Transition work

Course Book

Course book for 9618 specification.

Hodder Education: Cambridge International AS & A Level Computer Science Course Book.

This is the book we will be using from 2020 onward, as it is tailored towards the specific requirements of the course and offers a full structured approach to the CIE A level Computer Science 9618 course content.

The Hodder Education CIE Computer Science book for the new 2021 -2023 Specification. Available on paper and Kindle.

Computer Science A Level

Computer Science is an exciting, modern subject relevant to many disciplines and careers.

Almost every aspect of modern life involves computing; from cloud and internet use, through mobile devices and home appliances, to complex programs that help businesses and public services run smoothly. Vast networked systems of computers control global communication, trade, finance and transportation. Experience of Computer Science is relevant to all.

A good computer scientist wants to learn more about how computers work, to learn the language of code (C#) and to find ways to solve puzzles using logical thinking and mathematics. Our course offers a blend of practical coding and development experience with theory and discussion of how computers work and their impact on society. Computer Science is a creative subject that combines invention and excitement, that can look at the natural world through a digital prism.

Entry requirements

A minimum of 4 subjects at grade 5 or above at GCSE with a grade 5 in GCSE English Language and a grade 6 in Maths. GCSE Computer Science is not a prerequisite but is an advantage.

What will I study?

You will gain an understanding of different levels and types of programming languages and scripting. Strategies for problem-solving are studied, together with information management techniques. You will gain an understanding of computer hardware and software functionality as well as a detailed appreciation of how computer architectures operate. The course addresses all stages of the life cycle of computer software.

Units studied include:

Computer Systems

• Characteristics of processors, input, output and storage devices
• Software types and software development
• Networks and exchanging data (web, encryption and security)
• Data types, data structures and algorithms
• Legal, moral, cultural and ethical issues

Algorithms and Programming

• Elements of computational thinking (designing and coding in C#)
• Problem solving and programming (coding in C# and using LMC)
• Algorithms to solve problems and standard algorithms (e.g. sorting, traversal)

Method of delivery

You will be taught in well-equipped computer rooms for every session. Individual computers are available both in session and during study times to enable you to use online learning and resources effectively. Our A Level Computing team all bring experience from industry as well as years of teaching experience. Each member has experience of examination marking and/or external verification.

How will I be assessed?

OCR Computer Science A Level: Two x 150 minute exams plus 20% coursework (NEA).

Programming Project: The NEA (Non-Exam Assessment) coursework is a student-led experience of problem analysis, system design, software development and testing and evaluating. Your project will be of your own choice, assessed internally and moderated by an external examiner.

In the past students have produced exciting games, simulations, web applications and robot programs. Students will need to do autonomous research to develop more complex projects.

Good course combinations

This course combines well with most other A Levels and is particularly complemented by Maths, and sciences or Engineering. Other successful students have a strong background in creative or humanities subjects such as Design Technology and Media.

Your next steps

Computer Science is an extremely useful A Level, leading into a wide variety of computer-based disciplines, plus technologically rich subjects such as engineering or science. Computer Science skills and an understanding of technology are relevant to a wide range of careers and courses.

Students can progress into industry or apprenticeships to gain experience and qualifications as a Software Engineer, Software Developer, and a host of related roles. There is a significant shortage in Computer Science skills so your knowledge will be in demand! Students typically go on to study degree courses in:

• Computer Science
• Artificial Intelligence
• Computer Games Programming
• Cybersecurity
• Business Computing
• Engineering
• Mathematics
• Aeronautics

Computer Science is an area I have had interest in for a long time. The College course has been so worthwhile and interesting. The programming project in this course helps us to be prepared for the real world of work and the tutors here are really knowledgeable.

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75+ A-Level Computer Science NEA Ideas (and why they’re good)

In A-Level by Think Student Editor March 9, 2019 6 Comments

Computer Science at A-Level is sometimes misunderstood as being a subject where all you do is sit in front of a screen, coding away in Python, trying to build the next Google. While a lot of your time is spent staring at a computer screen, it’s not just about coding.

There is a theory side to Computer Science which plays a big role in determining what grade you get at the end of your two years. Your NEA will take a lot of analysis, planning and trial and error which many students do not expect. That’s why below I’ve provided a long list (in no particular order) of project ideas so at least one step is taken out of the equation. You can combine some of these ideas and create a Frankenstein-type project or maybe just take one and make it your own.

Remember, refer to the mark scheme to ensure you hit as many A-Level Computer Science skills as possible. It’s always worth taking a look at your relevant specification to see which skills you want to showcase, you can find specifications for OCR and AQA here. Without further ado, let’s get to it.

1. Maze Generation Software

There are many different algorithms that you could implement when programming a maze generator (like a lot). So, if you want a list on the different algorithms you could possibly implement, check out this article.

2. Rubik’s Cube Solver

This is probably the hardest project idea on this entire list – in terms of the actual implementation. Creating AI that can actually learn how to solve the Rubik’s cube is very, very difficult.

The good news however, is that I don’t think examiners will expect you to create AI that learns how to solve the Rubik’s cube entirely by itself. Therefore, if you do choose this idea, I highly recommend that you program your AI around one of the many pre-existing algorithms that have been created to solve Rubik’s cubes.

In my opinion, this is the best algorithm for you to base your AI around.

3. Bird Migration Pattern Predictor

If you actually pull this one off, I would eat my foot if you didn’t get top marks (an A*).

For this project, you will need to analyse how birds have migrated across the globe in the past. Then you will need to try and find correlations between migration patterns and geographic weather conditions. From this data, your program could predict future migration patterns depending on different climate changes.

I think a great start for this idea is to read into what web-scraping is and how to do it.

4. Nuclear Power Plant Meltdown Simulation

While programming this project, you would have simulate real world conditions. After you have created this Earth-like environment, you can model the effects that a nuclear power plant meltdown would have on said environment.

You could even add cities to see the affects that radiation would have on them too.

5. Supermarket Stock Management System

Supermarket’s not only need to manage stock, but also staff – both of which, they have lots of. This means that there is most definitely an opportunity for you to make a complex system that could aide a supermarket.

If you do choose this, make sure you read up on how a supermarket actually operates, so the system is suitable. There’s a great document here that should tell you all you need to know about managing a supermarket (and a lot more).

6. Restaurant Point Of Sale (POS) System

A point of sale system is very different to a stock management system (as you would find in a supermarket). The difference is that a point of sale system is used (guess what) at the “point of sale”, meaning staff will use the system at restaurant tables when taking food orders.

Therefore, you must make sure your POS system has an extremely friendly user interface, as customers don’t like waiting around!

7. Chess Playing AI

I don’t think I need to tell you that this is going to be challenging… Therefore, if done right, this could lead to a well earned A* for your NEA.

There are so many resources to help you develop this particular project idea online. So, whenever you get stuck, you will never be far away from help.

8. Image Recognition AI

I reckon this is probably equally as difficult as the Rubik’s cube one – AKA very, very hard.

This idea should be screaming at you: “machine learning and neural networks”. If it’s not, there might be something wrong with you…

Neural Networks + Machine Learning = High Marks

There are loads of free online resources that will help you a ton. However, I highly recommend that you get this book off Amazon.co.uk , it is the best book on getting started with neural networks that I have ever read – just going to have to trust me on this one.

9. Evolution Simulator

This project has the potential to be seriously complicated, however, you could also make it quite simple. It all depends on what’s evolving.

If you are going to simulate how animated stick figures get better at running over many generations, your program is going to be very complex. However, if you are going to simulate how a single-muscled slug can get better traveling between points as quickly as possible then it could be quite simple.

If you’re even considering this project, then you should definitely check out this YouTube playlist (it’s strangely satisfying watching his imaginary creatures evolve).

10. Voice Recognition AI

This project is (obviously) very similar to the image recognition project that was aforementioned. Therefore, this project too, should be screaming “machine learning and neural networks” at you.

I’ve never really programmed a voice recognition AI before, therefore, I can’t really recommend any specific books for you to get (as I can’t be certain of their quality). However, I have done a quick google search and within 5 minutes I can tell that there is shed loads of information on this topic, so on that front – don’t worry.

11. Sales Order Processing System (SOP)

An SOP system should, as the name suggests, manage sales. This means it should control the majority of communications between the warehouse, sales team and the client.

Below are things that a typical SOP system could do:

• Store Order History
• Generate Invoices
• Generate Reports
• Generate Delivery Notes
• Send Reminder Emails

You are tied down a bit with this project, as you do have to make sure a factory could actually use this software. However, there are still many different avenue’s for you take with the types of functionality you decide to implement.

12. Poker Game

For you to do this project, you would have to be fairly confident with networking. This game would allow multiple devices to join a “table” and start playing poker with each other.

Depending on how complex you want your program to be, you could add so many extra features. I think a great extra feature for this project would be to calculate the odds of someone winning per hand. Furthermore, you could also add a computer poker player (where you could definitely implement some AI).

13. DJ Software (Can Mix Music)

This one is definitely a fun project for those of you who have an affection for music. This project would clearly require you to learn a shed load about manipulating audio files, however, if you can pull it off I think you could really make a project that is A* worthy.

You could also build a control system which could implement the software. This might cost a bit of money, but once again, it’s going to make you like you really know what you’re doing.

14. Interactive Circuit Builder

If you want to know what I’m on about, get the free trial of Logicly or just go on YouTube and look at a video of someone else using Logicly.

Assuming you have done that, you will know what I mean by an “interactive circuit builder”. I would say that the most important aspect of this project would have to be the UI. Without a good user interface, the software would not be fit for purpose and you would definitely lose marks.

15. Quiz App

You could either make an offline quiz app or you make a much more complex client-server quiz style app. There is definitely much more opportunity to get an A* with the latter of those options.

If you decide to do a client-server model, I think a real time quiz app would work great – something (even remotely) similar to Kahoot would really stand out.

16. Software for Calculating The Big O of an Algorithm

Examiners will absolutely love this one, but why?

Because in doing this project, you would be making a computer science theory topic actually come to life. Therefore, if you do this project, you are showing to the examiner that you can get a concept off paper and actually make use of it in a real situation.

Besides that, this project is amazingly complex and will certainly provide you with plenty of opportunity’s for you to incorporate A* level concepts into your program.

If you have forgotten what Big O is, don’t worry (you should worry a bit actually) and just go give this a read.

17. Tracking And Monitoring Global Shipping Routes

This project is going to require you to get comfortable with web-scraping and API’s. You will need to be able to gather information about the global whereabouts of cargo ships frequently.

Once you have mastered the back-end tracking, you will need to think of a nice way to present the data. Maybe you could use certain programming libraries to make route representations on a global map?

18. Implementation of Machine Learning To Maximize Profits At An Airport

This could be my favorite project idea on here.

The lengths that airport companies go to when designing the layout of a particular airport is crazy. Everything is where it is for a reason: the route you take to board a plane, where you wait to board and the even where the security is. If you want more information about how airports maximize profits, check this out.

If you choose this project, I think you should do a simulation where people are represented by a particular sprite, shape or whatever you choose, and then they you follow them through the airport. After each day you could track the profits that the airport made.

Now this is where machine learning comes in… you could implement an algorithm that changes the layout of the airport each day and see if profits increase or decrease. Then the program would learn accordingly.

19. 3D First Person Shooter Game

Although many people choose to program a 2D game for their NEA, I think that programming a 3D game is just… better. Programming in 3D makes it so much easier for you to implement A* level programming techniques.

20. Implementation of AI To Model The Effects of Global Warming

Global warming is becoming an ever increasing issue in today’s world – so this project certainly checks the box “assists with a real world problem”.

Anyway, designing a program (using AI) that can attempt to predict what the effects of climate change are going to be on the planet is a great idea. It’s complicated enough, time-consuming enough and definitely “real worldy” enough.

A great place to start with this project is to check out the currently predicted effects of climate change, which you can find here.

21. Encrypted Instant Messaging App

An instant messaging app is one thing, but an encrypted instant messaging app is a whole different thing. This project is great because it just ticks so many boxes. You will be covering encryption and client-server networking in the same project!

Before you start this project, make sure you take out the different types of encryption methods (you can find some here).

22. E-Commerce Web App

Almost every single large company out there now has an online e-commerce website. Therefore, there is going to be plenty of helpful resources out there for you to learn from.

This project will also require some encryption as you will be dealing with payment methods such as debit and credit cards, which are VERY much confidential information.

23. Fitness Monitoring App

Programming a fitness app will allow you to actually interact with the hardware that is on the phone. For example, you could have a fitness app that tracks footsteps, in which case you would need to directly communicate with the phones pedometer.

24. Virtual Flashcard App

This can be a great project, if done right.

You’re going to have to get very good at databases if you do this project as a virtual flashcard app would require crap loads of them. A great example of a virtual flashcard app is Quizlet (I’m sure you have head of it already).

A simple virtual flashcard app should allow a user to:

• Create Folders For Different Subjects
• Create Flashcards Sets For Particular Modules
• Revise Flashcard Sets Effectively.

25. Public Transport Timetable App

Now, I don’t mean just display a PDF image of a pre-existing bus timetable and say “finished!”…

This app should be able to perform web-scraping on live bus and train timetables and display the information is a user friendly way.

Your program could even take two postal codes and calculate the quickest way to get there using a mixture of public transport and walking. It could also return the current price for that specific journey. An example of how this can be implemented is on the Stagecoaches “Plan A Journey” page.

26. Social Networking Platform

You all know what a social networking platform is. I don’t think I need to explain this one to you…

27. Physics Projectile Modelling Tool

If you are a fan of mechanics, this is your project. One of the many reasons this project is so good is because when programming it, you are forced to simulate a real world environment – in the sense that you program in gravity, terrain, air resistance etc.

Furthermore, if you were so inclined, you could very easily transform this project into a game, where you try to hit particular objects using a projectile. Angry birds is a great example of what I mean.

28. Nuclear Power Plant Management System

There’s more to managing a nuclear power plant than you think. Therefore, a nuclear power plant management system can either be super simple or extremely complex depending on what you choose to implement into the system.

I highly recommend you check out this link , it tells you all about the parts of a nuclear power station and you will get a feel for what your system will be managing very quickly.

29. Weather Forecasting Software

There are many paths you could take with this particular project, so it’s really down to what you decide. However, the fundamental core of this project is that you need to at least make an attempt at predicting what the weather will be like tomorrow, the day after or perhaps even a week from now.

You could implement some kind of machine learning algorithm that could compare what your weather prediction was and what the weather actually turned out to be like. From here, the algorithm could adjust the factors that went into making the prediction accordingly.

30. Air Traffic Controller AI

Air traffic controllers are essential to ensure that planes aren’t going to collide when coming in or going out of an airport. However, humans tend to make mistakes – fairly regularly. Maybe an AI would always get it right?

For this project, you would have to create a model of an airport and simulate planes coming in and leaving. Your, AI would ensure that no planes crash… hopefully.

31. Interpreter For Chosen Programming Language

Interpreters convert high level language code into machine code that can be directly processed by the CPU. Furthermore, interpreters normally translate code per line, not all at once.

Although this programming project is challenging, you might struggle to incorporate some of the A* level programming concepts in your code. All I’m saying is that make sure you keep an eye on the marking criteria and don’t forget why you’re doing this project – to get the grades!

32. Internet Speed Tester

There’s more that goes into getting an accurate assessment of your internet bandwidth than you think. Therefore, making an internet speed test is definitely complex enough.

For this project, you will need to add feature to bulk it up. You could maybe try different methods of testing internet speed then compare how accurate each of them are.

33. Secure FTP Server

FTP stands for File Transfer Protocol. So this project would basically be making software that allows devices to easily transfer files between each other. I know I’ve said this a lot, but, once again, this project is going to be as complex as you make it.

If you choose this project, make sure you don’t just use an FTP library that does everything for you! Try and do as much as possible by yourself.

34. Software To Find The Best Online Deals

For this project, you’re going to need to “scrape” all of the current prices for a particular product off their respective websites. That’s the hard part. Next, you will have to present all of your various comparisons to the user in an easy-to-understand way (and give a conclusion containing where they can find the cheapest price).

A great example of this type of software is the website Trivago.

35. AI Chat Bot

This project would entail you creating a program that can talk to humans as if it was a human too. If there was such thing as a perfect AI chat bot, you shouldn’t be able to distinguish it from a human.

When programming this, you are going to need to be able to program in some sort of artificial intelligence that can learn from previous conversations it had with real people.

Two examples of chat bots that I have seen before are CleverBot,   Eviee, and more recently ChatGPT.

36. Search Engine

Examples of search engines are: Google, Bing and Yahoo. There role is to receive a query from a user and index webpages in accordance with how relevant they are to the particular query. So if you googled “what is a pineapple?”, the idea is that a webpage containing information about pineapples would come up first before information about bananas.

There are many factors to consider when ranking webpages. Possible ranking factors for your SE could be:

• Keyword Frequency
• Image ALT Tags
• How Users Have Interacted With Page Previously.

37. AI Spam Filter

If you’ve ever been directly (or even indirectly) involved in front-end website development or survey development, you will know how big of a problem spam is. Spam messages can take many forms and with each passing year, it is getting more and more difficult to decypher what messages are genuine and which are spam.

This means that for your A-Level Computer Science NEA project, an idea could be to build a spam filter that could be run on an email server, implementing AI and Machine Learning. There is huge potential with this project idea and it is certainly not an easy one to develop!

38. Music Suggestion Tool

We’ve all used and heard of the famous YouTube recommendation service… Every time you go on YouTube, they have an algorithm running that recommends videos based on what they think you’ll like. Why not make your own version but just for music?

You could even tailor the recommendations to what mood the person is in by analysing music videos for particular themes e.g. sad, happy or exiting. If you did decide to go down this route with your NEA project, there is huge potential with this idea for machine learning implantation which would be designed around user feedback (user specifies whether or not the recommendation was good).

There is a great video on how the YouTube recommendation algorithm works here.

39. Graph Plotting Software

If you’re currently studying A-Level Maths or A-Level Further Maths, you will know the importance of graph plotting software is very high. So, there’s demand, why not provide the supply in the form of an NEA computer science project?

Your project could receive a polynomial expression as an input, and output (plot) a visual graphic of that graph… There are many examples of these types of software out there, one that you should check out is GeoGebra .

40. Foreign Language Teacher

This project idea could be made extremely basic, or extremely advanced. However, the fundamental building blocks of this project idea will always be the same; it will assist users in learning a foreign language. I don’t think I need to say too much about this idea, but I would recommend you checkout examples of this type of software such as Babbel or Duolingo.

41. Sat Nav

This NEA project could potentially consist of both web-scrapping and Dijkstra’s algorithm. That is a seriously nice combination!

What is not immediately obvious about this project idea is how much graphical work there is to it – there’s a lot. All I’m saying is that if you do decide to choose a project idea similar to this one, be sure that your graphical skills are very strong!

The most obvious example of software similar to what’s mentioned above is Google Maps, go check it out , if you’re interested.

42. Make Your Own IDE

Now this might seem intimidating at first but hear me out. There’s lots of resources out there to help you out on this project and it allows you to be as creative as you want since you’re the designer. You should be able to run, debug and compile the code.

You can use this video and this article to get you off to a good starting point.

43. 2D Platformer Game

This A-Level NEA project allows you to be as creative and go into as much detail as you want. You could include enemies, randomly generated levels, level editors where the player could make their own levels, multiplayer capabilities etc. One of the more challenging things you could do is include the ability to save your position and access it later.

This project will really get your creative juices flowing as, even if someone has the same idea as you, your games could come out wildly different. You can find many game making tutorials, particularly in Python. You may have heard of the popular library pygame which most games in Python are based on. You can click here to find a tutorial on the basics of pygame.

44. 3D Platformer Game

This will certainly push you into the top marks as it requires a deeper understanding of how to render vector graphics and some maths. Remember, the examiners aren’t worried about how good the game looks, they want to know about the complexity of your code and the skills you showcase within it. Some of the most popular libraries include OpenGL (in C/C++) and Panda 3D (Python).

One of the advantages of doing a 3D game is that the game itself doesn’t actually need to be very complicated. If all goes well, the complexity should come from the 3D rendering, meaning your game could be relatively simple.

45. Revision Aid

This idea is very popular amongst students as they likely already use one, or are taking this opportunity to build their own. This can be anywhere from a flashcards application to a quiz or a game where you have to dodge the wrong answers. See Quizlet or Anki for inspiration.

As with the platformer, the scalability of this project is up to you and how complex you want to make it. Maybe you want to have a competition element where users get a score for how many questions they get right. This project will require a knowledge of databases (e.g. SQL) so if that’s something you’re not good with then there’s still a few more to go.

46. Circuit Simulator

This project is heavily centred around a good-looking GUI, so you will need to have an immense amount of self-control to ensure you don’t throw away hours and hours into a part of the code that barely gets you any marks.

The idea is based around an interactive, online version of a circuit builder, allowing users to connect resistors, lamps and other electrical things I don’t know the names of using wires. You may want to make use of TKinter , a python library, to help with your GUI.

47. Live Chat Forum/Room

This one is pretty self-explanatory but requires a deep knowledge of networking and client-server communications. There are many tutorials you can find online on how to create chat software which is where your creativity will need to come in.

You could think about allowing users to send pictures, create their own group chats, send videos etc. You could even create an AI moderator which censors inappropriate language or detects inappropriate pictures and takes them down.

48. Robotics

This seems quite vague but what I mean is using code to control and communicate with a robot that serves a certain purpose. For example, you could code a robot vacuum to detect walls or the size of the room, where dirt is etc. You can do this through image recognition which by itself is very complex and high level, securing you those marks.

The biggest thing with this is that it requires you to have access to the required hardware so you can check if it works correctly. With the robot vacuum idea, you’re going to need to have a robot vacuum on hand.

49. Business Rota Application

Some of you might have part-time jobs, in which case you will have a better idea of what this is. In order to make sure too many people aren’t working the same shift at once, businesses often have a rota which keeps track of who goes where and at what time.

You could create a database with a simple GUI which considers new employees and their shifts and orders them accordingly. This ensures shifts aren’t clashing or overlapping. You could make this as customisable as you want to where it could apply to any business who have any number of employees working at one time or several related times.

You may need to get into contact with a real business and analyse their current system. That way, you can find anything wrong with it and improve upon it. It also means you have a bit less work to do because you aren’t starting from scratch.

50. Recreate a Classic / Retro Game

This takes away the element of coming up with brand new game logic. Instead, you have the rules laid out for you and you just have to follow them. However, there is a definite danger of copying and pasting premade code as the game already exists. Try to add your own twist to the game.

For example, you could remake Pacman but instead of having the ghosts controlled by AI, you could have them be controlled by other users. Not only is this complex, but it also ensures your code isn’t identical to the original game. There’s a whole library dedicated to retro game making in Python which you can find here .

51. Weather Forecaster

As boring as it sounds, it has the potential to get you into that high grade band. It may require some web-scraping and you might want to build your own site to display this info. You could show the predictions for the weather on this site and you could allow the user to enter their email to be sent alerts or notifications if extreme weather is to occur.

52. GPS App

Here’s your chance to implement all those path-finding algorithms your teacher might have been telling you about (I’m looking at you Dijkstra ). You can implement this in different ways, whether it’s the “Google Maps” approach where the user defines a destination or the “Find My iPhone” approach where the destination is unknown by the user until the app is activated. Maybe they want to put a GPS on their kid’s device or their own device.

53. Meteor Trajectory Simulator

If you like space or physics, this one is for you. You can really go wild with this in terms of the GUI and the back-end code. It will need a lot of complex mathematical formulae in order to function correctly, but it will be worth it when you get that top A-Level grade. That’s why having at least some interest in mathematics will benefit you in this project. You’ll be working with a lot of numbers whether that’s calculating velocity or determining the angle of a meteor.

54. 2D Shooter

This is similar to the platformer except the focus will be on the shooting aspect. You could use AI to control the enemies and maybe include different levels of guns that do different damage. You could even do a boss battle. Refer to NEA idea two to find a pygame tutorial which should give you a good base on making the game.

55. Street Fighter Remake

If you’ve ever played or heard of street fighter, you know what you need to know. However, for the three people at the back who have never heard of it, it’s a 2D fighter game. You can customise this however you want and include power ups, boss fights etc. You may need to look at the code of several other similar games to combine them and make your own.

56. Finding the Shortest Route on the London Underground

This project will allow you to use the path finding algorithms and maybe a website. You can calculate the shortest distance between two stations and calculate the time taken to get there. You will probably need to do some research on JavaScript in order to get the backend of your website working. I’ll link a website tutorial here to get you started.

57. Workshop / Club Booking Timetable

Similar to the rota system, this project will ensure that two people are not booked at the same time on the same day. This will require a knowledge on relational databases, namely SQL which, at this point in your A Level, you should know a bit about. If not, there’s a quick project you can do to get yourself familiar with queries, primary keys, foreign keys etc.

58. Visualising the Spread of a Disease

You could web-scrape here and show on a map of the world and the associated deaths from a certain disease. In other words, you could for example show hot spots for the disease in reds or oranges and leave the others as white. Web scraping is a relatively easy thing to learn and can be extremely powerful, even outside of your A-Level. Here’s a quick tutorial to get you started. The complexity will come from how you present the data you’ve scraped.

59. Plane Seat Booking System

This will be like the workshop booking system in that you need databases to store the customer’s information. You would ensure that one seat is not offered to two people at once. You could even keep track of the details of loyal customers and offer them first class tickets or other deals.

60. Stock Management System

This would be a database which stores the amount of stock a business has. You could produce sales reports for the most popular items or see which items are low in stock. There are many combinations of ways you could output this information (e.g. a report, website, email). Just ensure it is more complex than placing the output in the terminal.

61. Traffic Light Controller

This project entails coding an AI to ensure that cars don’t collide. You could possibly set it up where, if there’s an ambulance, you give it all green lights. You might even want to use image recognition based on a satellite image of a city and gather the locations of the traffic lights on that image. That would really push your grade up as, instead of using a built in library, you can “teach” your AI what traffic lights look like. Find a video tutorial on machine learning in Python here .

62. Coupon Collector

If you’ve ever heard of “Honey”, you’ll know the gist of this project. You will have to scrape the internet for coupons for a certain website specified by the user. The code could automatically test these coupons and output the cheapest one. See number 17 for a website scraping tutorial.

63. Facial Recognition Software

This project seems complex but that’s a good thing if you want the highest grade. This has a variety of purposes as many of you are likely familiar with the face recognition on many phones. Read this article o n how the basics of how to do it in Python and find out more.

Make sure you aren’t just relying on built in libraries to handle the complex algorithms because all those marks will disappear. You have to write the code yourself and typing “import facialRecognition” doesn’t count, as sad as that is.

64. Chess Over Two Computers

Here you can include networking and client-server communication (both of which are references in the A-Level Computer Science specification). There is a possibility to include AI which detects automatically if there is a check or checkmate. This would require you to keep track of the ending positions of each piece and know what constitutes as a check for example. Most turn-based games rely on a sort of algorithm which you can find out more about here .

65. Sudoku Solver

This requires intense programming and AI but will totally be worth it by the end. You could give the user the opportunity to try and solve it themselves at first then, afterwards, give them the answer. You could also set a time limit, you could have a scoreboard, there’s lots of things you could do with it. Also, you may want to have the unsolved puzzle be randomly generated which adds a whole new layer of complexity. Computerphile has a great video on this exact subject in Python.

66. Social Media Specifically for Students in the Same College or University

A social media idea has already been suggested but you may want to make one specifically for your college. The students could input their timetables and the code could suggest other students with the same timetable. That way, they can meet during their mutual break time. You could also include group chats for specific subjects at your college.

67. Fantasy Football Team

Web scraping is going to be a major concept in this project unless you want to hard code in every footballer on every team. You could set up a network where fantasy teams can “play” against each other and winners get more points. The user can customise their own team and earn points. You can then display it in a website or another GUI like TKinter.

68. Planet Orbit Simulator

This one goes out to the physics and maths students again. Allow the user to change the size, direction and colour (why not?) of planets and calculate the trajectory of their new orbit. This would entail many mathematical calculations so, if you like this sort of thing, this is for you. It also gives you the chance to use and render 3D graphics in order to visualise the planets for the user.

Take a look at the game Kerbal Space Program for an advanced implementation of this idea!

69. Pathfinding Comparer

Here, you would test and visualise the efficiency of certain pathfinders in different situations. For example, the user could place certain obstacles between two points and then employ the Dijkstra and A star path finders. You can find what I mean in a tutorial here . There are many, many, many pathfinders you can compare so you can really pick whichever ones you would like. I won’t list them all here, but you can find a some of them through this link .

70. Finding Shortest Path on a College / University Campus

With this project, you would need to create a graph with each node corresponding to the buildings or departments on the map. This would make more sense if you choose a college or university that has a big campus that spans over a large geographical area. It may end up being very useful for those students who have 5 minutes to speed walk all the way across their campus. The heuristic or weight of each edge could be determined by many things (e.g. whether you have to cross a road, if you have to go through a certain building with stairs etc).

71. Solitaire

This popular card game might be simple to code but to add that layer of complexity, you can include the option for an AI to complete the game for the user. It needs to be able to recognise if the game is completable though.

72. Password Manager

Think “LastPass” or “DashLane”. You securely store and encrypt your user’s passwords and, if you wanted to, you could include a password suggestion element where the application offers a potential strong password to the user. This takes away the need for the user to memorise their passwords and think of a way to make it stronger. You can find an example here and extra info here .

73. Simple Board Game

You might want to come up with your own board game or copy another anywhere from Scrabble to Monopoly. This will take a lot of time and consideration into how you would like it to work. You may want to set up a tutorial or make it multiplayer against other humans (this might be your chance to include AI)

74. Cash register

A cash register would be great as you can base it off pre-existing cash registers in terms of the functionality. It offers a web version of a cash register that would be used by small businesses. This means you could contact small businesses in your area and cater to their needs. It may track sales, inventory and checkout credit cards. The options for what you want the cash register to do are completely up to you and your client’s needs.

This kind of goes under the retro games column however, there is the potential for AI to be implemented. You could program the AI to play the most efficient move and get the most points. The best way to go about this is to code the game by itself first the add the AI afterwards. You can even apply a competitive element by having a score system via relational database or multiplayer functionality.

76. Pacman Recreation

You can use AI to control the ghosts and, to really push yourself, you can add difficulty levels to these ghosts. Maybe the longer/more a user plays, the harder the ghosts get. You can increase their difficulty by making them faster or making them “smarter”. This would require path-finders to find the shortest path from the ghost to the player.

The Importance of Mark Schemes and Specifications

The mark schemes and specifications for A-Level Computer Science will be your best friends throughout your whole coursework experience. Though they can sometimes be vague, you should be working closely with them to ensure your project hits all the points you need so you can collect those marks. Good luck!

• AQA Computer Science Mark Scheme
• OCR Computer Science Mark Scheme

nice project

the exemplar is motion control and thats bares hard

bruh what do i put as stakeholders for the rubiks ai

Your idea is brilliant and many puzzle solvers are going to really benefit from your programme, and for that reason, I’m out.

Hi i was just wondering how i could make the (“visualizing the spread of a disease”) program to show a large amount of skill as I worry that there wont be enough coding involved to showcase a lot of skill.

Programmes & Qualifications

Cambridge international as & a level computer science (9618).

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A level Computer Science

Why study a level computer science.

A level Computer Science encourages learners to meet the needs of Higher Education courses in computer science as well as those of 21 st  century digital employers. It encourages learners to think creatively, through applying practical programming solutions, demonstrating that they are effective users of technology. They will also be able to appreciate the ethical issues that arise with current and emerging computing technologies.

How we use computers and computer programs has utterly defined the world we live in today and it is computer scientists who connect the abstract with reality, creating the products we use daily. With its foundations in Maths, Computer Science spans hardware and software engineering, the user interface, and computer technology’s expansion into new areas.

‘Whether you want to uncover the secrets of the universe, or you want to pursue a career in the 21 st  century, basic computer programming is an essential skill to learn.’  Stephen Hawking.

Note that our experienced  University Services Adviser  can advise on  A level courses  and all aspects of university entrance.

SEE OUR IGCSE & A LEVEL  EXAM RESULTS

Wolsey Hall is a registered online Cambridge International School.

We offer a wide range of A level courses.

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What do I need to know to enrol?

We strongly recommend that students have studied Computer Science at IGCSE/GCSE Level and achieved a Grade C or 5. If students have not studied Computer Science at IGCSE, it is desirable that they have previous experience of programming. Problem solving ability is essential for this course, so we do require students to have Grade B or 6 in Maths at IGCSE/GCSE Level prior to embarking on the course. All students undertaking Wolsey Hall A levels must also have an IGCSE/GCSE in English Language at Grade C or 4.

Exam and syllabus information

This A level Computer Science course prepares you for the Cambridge AS and A level syllabus 9618. Exams take place in June and November.

The full Advanced level qualification comprises AS and A level.

Theory Fundamentals worth 50% of your AS grade and 25% of your overall A level grade. (1 hour 30 minutes)

Fundamental Problem-solving and Programming Skills worth 50% of your AS grade and 25% of your overall A level grade. (2 hours)

For the full  A level in Computer Science  you will sit two additional papers:

Advanced Theory worth 25% of your overall A level grade. (1 hour 30 minutes)

Practical worth 25% of your overall A level grade. (2 hours and 30 minutes)

*Please note: Paper 4 is a practical paper and will require use of a computer (offline). Please check with your exam centre that offer this service to private candidates.

There are Cambridge exam centres in over 150 countries. We can provide details of the most convenient.

All of our A level courses include a number of past exam papers in the final module. These include the most recent paper which can be taken as a mock exam and submitted to your Tutor for assessment and feedback for a modest additional fee.

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A level Maths

A Level Maths is an interesting and challenging course which extends the methods you learned at (I)GCSE and includes optional applications of mathematics, such as Statistics and Mechanics. Statistics is

A level Further Maths

The Cambridge A Level Further Maths allows you to develop skills which will help you study a range of STEM subjects at a higher level. It strengthens transferrable skills such as logical thinking, modelling and analysis. It is also highly valued when applying to university for competitive courses such as Medicine, Computer Science and Engineering.

A level Physics (UK)

A Level Physics is a mixture of highly conceptual thinking and very practical applications. You need to be able to think about abstract ideas such as fields, but be able to apply those ideas to how, for instance, electric motors work.

A level Chemistry (UK)

Our A level Chemistry course shows students that Chemistry is all around us. The world is filled with materials that have been discovered, developed and tested by chemists, such as medicines, foods, fuels, plastics, fertilisers and fabrics. An understanding of the subject can help you answer many questions about everyday life!

The initial study advice I received was easy to understand. My Tutors were more than helpful and were quick to answer any of my questions and grade my assignments. My Student Progress Manager was excellent in not only guiding me but keeping me up to date on events and other stuff also.

Jin Bo-Kyung, A Level Student

South Korea

If you’re thinking of enrolling your child at Wolsey Hall Oxford and you’d like to know more about what we do or how to enrol, please get in touch. We’re ready to enrol new students throughout the academic year.

Systems architecture in A Level computer science

CP505 Live remote training course

During this course you'll explore the structure of the internal components of a computer system. In addition you'll explore the von Neumann architecture and fetch-execute cycle.

• Live remote training 25 April 15:30—25 April 2024
• Live remote training 8 May 13:00—8 May 2024
• Live remote training 16 May 08:00—16 May 2024
• Live remote training 28 May 16:00—28 May 2024
• Live remote training 5 June 09:30—5 June 2024
• Live remote training 10 June 14:00—10 June 2024
• Live remote training 20 June 15:30—20 June 2024
• Live remote training 1 July 14:00—1 July 2024
• Live remote training 11 July 09:30—11 July 2024
• Live remote training 23 July 13:00—23 July 2024

Unlock the inner workings of computer systems during this course. Delve into the purpose and function of key system components, gaining insight into how they impact overall performance and functionality. Master the fundamentals of Von Neumann architecture and the fetch-decode-execute cycle. You’ll evaluate the factors influencing CPU performance through the use of a real-world scenario.

Discover the intriguing distinctions between Von Neumann and Harvard processor architectures, and explore the pivotal role of GPUs as co-processors. Investigate the applications of both RISC and CISC processor designs, and examine their key differences. Through the exploration of a variety of online resources, engagement in professional discussions with educators alongside practical experience of exam questions, emerge from this course best equipped to support student success within the topic of systems architecture.

Who is it for?

This course is aimed at teachers delivering A Level computer science. It is advised you have some basic knowledge of systems architecture from GCSE computer science specifications.

During this course you’ll access the Isaac Computer Science platform , it is advised you sign up for a free, teachers account ahead of the course.

Topics covered

Key system components – during this session, you will discover the vital system components that power your computer's performance. You will explore models of the Von Neumann architecture and investigate the fetch-decode-execute cycle. You’ll analyse and evaluate the factors affecting CPU performance using a real-world scenario.

Processor architectures – during this session, you will explore a variety of processor architectures. You will uncover the distinctions between Von Neumann and Harvard designs, unveiling the core of computing innovation. You will dive into the fascinating world of GPUs and their pivotal role as co-processors, before investigating the differences between RISC and CISC architectures.

How long is this course?

This course will last approximately 2.5 hours, these sessions maybe split across multiple days.

How will you learn?

Scheduled live, interactive online sessions led by an experienced practitioner. Flexible Professional Development Leader-supported, participant-led tasks, involving deep exploration of the subject content.

By the end of this intensive CPD pathway you will be able to:

• Demonstrate understanding of computer system components and their impact on performance and functionality
• Explore Von Neumann architecture and evaluate the factors affecting CPU performance
• Effectively differentiate between processor architectures, including Von Neumann vs. Harvard and RISC vs. CISC

This course is part of Teach secondary computing

Teach secondary computing

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Online A Level Computer Science

Description.

Our online Computer Science A Level course is meticulously designed to equip students with a comprehensive understanding of computational thinking, problem-solving, and the development of computer-based solutions. This cutting-edge A Level computer science online curriculum dives deep into algorithms, programming languages, and the ethical implications that arise in the realm of current and emerging computing technologies.

Additionally, the course provides a robust foundation in Information representation, communication and Internet technologies, hardware, software development, and relational database modelling. If you’re looking to gain an edge in the ever-evolving tech industry or pursue further studies in Computer Science, this course offers you a ticket to a bright future.

Homework, Assessment and Reporting

Students enrolled in our A Level computer science course online are expected to complete at least one piece of homework per subject each week. To maximise success, it’s imperative to revise class notes and solidify one’s understanding after each lesson. The rule of thumb is to dedicate an hour of independent study for every hour of in-class instruction.

Assessment is a structured process with Level 5 internal assessments occurring in June and Level 6 internal mock assessments scheduled for November and March. Following these assessments, comprehensive reports are issued. These reports include grades for both attainment and effort, along with valuable written feedback from Success Coaches and the Head Teacher, at the end of the Autumn and Summer terms for Level 5 and after the mock assessments for Level 6.

Parental Engagement

Parents are highly encouraged to actively participate in their child’s educational journey. Our unique family Teams account enables parents to maintain an ongoing dialogue with teachers throughout the academic year. This provides a more detailed tracking of student progress, far exceeding what a typical annual parent consultation evening could offer.

Embark on an intellectually stimulating journey with our A Level Computer Science online course and prepare for a future where technology is omnipresent.

Click here to see this year’s Assessment and Reporting schedule

Students will gain knowledge and understanding of Computer Studies by studying the key topics – see ‘Key Topics’ section below. Students gain technical skills, as well as being able to effectively test and evaluate computing solutions. Studying A Level Computer Science will help students appreciate computing technologies, how they can be used and the potential risks.

1. Theory Fundamentals

1.1 Information representation

1.1.1 Number representation

1.1.2 Images

1.1.3 Sound

1.1.4 Video

1.1.5 Compression techniques

1.2 Communication and Internet technologies

1.2.1 Networks

1.2.2 IP addressing

1.2.3 Client- and server-side scripting

1.3 Hardware

1.3.1 Input, output and storage devices

1.3.2 Main memory

1.3.3 Logic gates and logic circuits

1.4 Processor fundamentals

1.4.1 CPU architecture

1.4.2 The fetch-execute cycle

1.4.3 The processor’s instruction set

1.4.4 Assembly language

1.5 System software

1.5.1 Operating system

1.5.2 Utility programs

1.5.3 Library programs

1.5.4 Language translators

1.6 Security, privacy and data integrity

1.6.1 Data security

1.6.2 Data integrity

1.7 Ethics and ownership

1.7.1 Ethics

1.7.2 Ownership

1.8 Database and data modelling

1.8.1 Database Management Systems (DBMS)

1.8.2 Relational database modelling

1.8.3 Data Definition Language (DDL) and Data Manipulation Language (DML)

2. Fundamental Problem-Solving and Programming

2.1 Algorithm design and problem-solving

2.1.1 Algorithms

2.1.2 Structure chart

2.1.3 Corrective maintenance

2.1.4 Adaptive maintenance

2.2 Data representation

2.2.1 Data types

2.2.2 Arrays

2.2.3 Files

2.3 Programming

2.3.1 Programming basics

2.3.2 Transferable skills

2.3.3 Selection

2.3.4 Iteration

2.3.5 Built-in functions

2.3.6 Structured programming

2.4 Software development

2.4.1 Programming

2.4.2 Program testing

2.4.3 Testing strategies

3. Advanced Theory

3.1 Data representation

3.1.1 User-defined data types

3.1.2 File organisation and access

3.1.3 Real numbers and normalised floating-point representation

3.2 Communication and Internet technologies

3.2.1 Protocols

3.2.2 Circuit switching, packet switching and routers

3.2.3 Local Area Networks (LAN)

3.3 Hardware

3.3.1 Logic gates and circuit design

3.3.2 Boolean algebra

3.3.3 Karnaugh Maps

3.3.4 Flip-flops

3.3.5 RISC processors

3.3.6 Parallel processing

3.4 System software

3.4.1 Purposes of an operating system (OS)

3.4.2 Virtual machine

3.4.3 Translation software

3.5 Security

3.5.1 Asymmetric keys and encryption methods

3.5.2 Digital signatures and digital certificates

3.5.3 Encryption protocols

3.5.4 Malware

3.6 Monitoring and control systems

3.6.1 Overview of monitoring and control systems

3.6.2 Bit manipulation to monitor and control device

Computer, broadband internet connection

It is the parents’ responsibility to arrange their child’s examinations; our teachers will provide all the support required. Most students will sit their examination papers at a school or college who accept private candidates. Some students sit their examinations at private examination centres.

If you are intending to study A Level Computer Science, we recommend that you spend some time in the summer holidays preparing.

Work through the Java Script tutorials on W3 Schools: JavaScript Tutorial

What skills will students develop in the A Level Computer Science online course?

The A Level Computer Science online course is designed to help students enhance their computational thinking and problem-solving skills. They will learn how to develop solutions using algorithms and various programming languages. Students will also understand the ethical considerations that accompany current and emerging technologies.

What topics are covered in the Computer Science A Level course?

The course dives into various subjects such as information representation, communication and Internet technologies, hardware, software development, and relational database modelling. It aims to provide a comprehensive understanding of these areas, helping students gain both knowledge and practical skills.

What is the assessment structure for the online Computer Science A Level?

Students in the sixth form are required to complete a minimum of one piece of homework per subject weekly. Internal assessments occur in June, November, and March. Reports are then issued twice a year and comprise grades for both attainment and effort, accompanied by written feedback from the educators.

How is progress monitored in the Computer Science A Level online course?

Parents can engage in continuous dialogue with teachers through their family Teams account, which allows for more thorough tracking of a student’s progress throughout the year compared to a single annual consultation evening.

What equipment is needed for the Computer Science A Level online course?

The teachers.

Computer Science at Cambridge Home School Online is taught by Mr Evans and Mr Descombe. Click on the names below to find out more about our Computer Science teachers.

How to apply

Our school is nearly always full, with very few school places!

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As and a level computer science - h046, h446, specification at a glance, assessment overview.

Students must take all three components to be awarded the OCR A Level in Computer Science.

* Indicates the inclusion of synoptic assessment.

Content overview

Component 01: computer systems.

Students are introduced to the internal workings of the (CPU), data exchange, software development, data types and legal and ethical issues. The resulting knowledge and understanding will underpin their work in component 03.

• The characteristics of contemporary processors, input, output and storage devices
• Types of software and the different methodologies used to develop software
• Data exchange between different systems
• Data types, data structures and algorithms
• Legal, moral, cultural and ethical issues.

Component 02: Algorithms and programming

This builds on component 01 to include computational thinking and problem-solving.

• What is meant by computational thinking (thinking abstractly, thinking ahead, thinking procedurally etc.)
• Problem solving and programming – how computers and programs can be used to solve problems
• Algorithms and how they can be used to describe and solve problems.

Component 03: Programming project

Students are expected to apply the principles of computational thinking to a practical coding programming project. They will analyse, design, develop, test, evaluate and document a program written in a suitable programming language. The project is designed to be independently chosen by the student and provides them with the flexibility to investigate projects within the diverse field of computer science. We support a wide and diverse range of languages.

Students must take both components to be awarded the OCR AS Level in Computer Science.

* Indicates the inclusion of synoptic assessment

Component 01: Computing principles

Students are introduced to the fundamental technical principles of computing.

This component covers:

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AS and A-level Computer Science

• Specification
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• Introduction
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• 3.1 Fundamentals of programming
• 3.2 Fundamentals of data structures
• 3.3 Systematic approach to problem solving
• 3.4 Theory of computation
• 3.5 Fundamentals of data representation
• 3.6 Fundamentals of computer systems
• 3.7 Fundamentals of computer organisation and architecture
• 3.8 Consequences of uses of computing
• 3.9 Fundamentals of communication and networking
• 4.1 Fundamentals of programming
• 4.2 Fundamentals of data structures
• 4.3 Fundamentals of algorithms
• 4.4 Theory of computation
• 4.5 Fundamentals of data representation
• 4.6 Fundamentals of computer systems
• 4.7 Fundamentals of computer organisation and architecture
• 4.8 Consequences of uses of computing
• 4.9 Fundamentals of communication and networking
• 4.10 Fundamentals of databases
• 4.11 Big Data
• 4.12 Fundamentals of functional programming
• 4.13 Systematic approach to problem solving

4.14 Non-exam assessment - the computing practical project

• Scheme of assessment
• Non-exam assessment administration
• General administration

Purpose of the project

The project allows students to develop their practical skills in the context of solving a realistic problem or carrying out an investigation. The project is intended to be as much a learning experience as a method of assessment; students have the opportunity to work independently on a problem of interest over an extended period, during which they can extend their programming skills and deepen their understanding of computer science.

The most important skill that should be assessed through the project is a student's ability to create a programmed solution to a problem or investigation. This is recognised by allocating 42 of the 75 available marks to the technical solution and a lower proportion of marks for supporting documentation to reflect the expectation that reporting of the problem, its analysis, the design of a solution or plan of an investigation and testing and evaluation will be concise.

Types of problem/investigation

Students are encouraged to choose a problem to solve or investigate that will interest them and that relates to a field that they have some knowledge of. There are no restrictions on the types of problem/investigation that can be submitted or the development tools (for example programming language) that can be used. The two key questions to ask when selecting a problem/investigation are:

• Does the student have existing knowledge of the field, or are they in a position to find out about it?
• Is a solution to the problem/investigation likely to give the student the opportunity to demonstrate the necessary degree of technical skill to achieve a mark that reflects their potential?

Some examples of the types of problem to solve or investigate are:

• a simulation for example, of a business or scientific nature, or an investigation of a well-known problem such as the game of life
• a solution to a data processing problem for an organisation, such as membership systems
• the solution of an optimisation problem, such as production of a rota, shortest-path problems or  route finding
• a computer game
• an application of artificial intelligence
• a control system, operated using a device such as an Arduino board
• a website with dynamic content, driven by a database back-end
• an app for a mobile phone or tablet
• an investigation into an area of computing, such as rendering a three-dimensional world on screen
• investigating an area of data science using, for example, Twitter feed data or online public data sets
• investigating machine learning algorithms.

There is an expectation that within a centre, the problems chosen by students to solve or investigate will be sufficiently different to avoid the work of one student informing the work of another because they are working on the same problem or investigation. Teachers will be required to record on the Candidate Record Form for each student that they have followed this guideline. If in any doubt on whether problems chosen by students have the potential to raise this issue, please contact your AQA adviser.

Table 1 and Table 2 show the technical skills and coding styles required for an A-level standard project. If a problem/investigation is selected that is not of A-level standard then the marks available in each section will be restricted.

Project documentation structure

The project is assessed in five sections. The table below lists the maximum available mark for each section of the project:

For marking purposes, the project documentation should be presented in the order indicated in the table above. The table does not imply that students are expected to follow a traditional systems life cycle approach when working on their projects, whereby a preceding stage must be completed before the next can be tackled. It is recognised that this approach is unsuited to the vast majority of project work, and that project development is likely to be an iterative process, with earlier parts of the project being revisited as a result of discoveries made in later parts. Students should be encouraged to start prototyping and writing code early on in the project process. A recommended strategy is to tackle the critical path early in the project development process. The critical path is the part of the project that everything else depends on for a working system or a complete investigation result to be achieved.

Using a level of response mark scheme

Level of response mark schemes are broken down into a number of levels, each of which has a descriptor. The descriptor for the level shows the average performance for the level. There are a range of marks in each level. The descriptor for the level represents a typical mid-mark performance in that level.

Before applying the mark scheme to a student’s project, read it through and annotate it to show the qualities that are being looked for. You can then apply the mark scheme.

Step 1 Determine a level

Start at the lowest level of the mark scheme and use it as a ladder to see whether the performance in that section of the project meets the descriptor for that level. The descriptor for the level indicates the different qualities that might be seen in the student’s work for that level. If it meets the lowest level then go to the next one and decide if it meets this level, and so on, until you have a match between the level descriptor and the work. With practice and familiarity you will find you will be able to quickly skip through the lower levels of the mark scheme.

When assigning a level you should look at the overall quality of the work rather than any small or specific parts where the student has not performed quite as the level descriptor. If the work covers different aspects of different levels of the mark scheme you should use a best fit approach for defining the level and then use the variability of the response to help decide the mark within the level. ie if the response is predominantly level 3 with a small amount of level 4 material it would be placed in level 3 but be awarded a mark near the top of the level because of the level 4 content.

Step 2 Determine a mark

Once you have assigned a level you need to decide on the mark. The exemplar materials used for standardisation will help. This work will have been awarded a mark by AQA. You can compare your student’s work with the exemplar to determine if it is the same standard, better or worse. You can then use this to allocate a mark for the work based on AQA's mark on the exemplar.

You may well need to read back through the work as you apply the mark scheme to clarify points and assure yourself that the level and the mark are appropriate.

Work which contains nothing of relevance to the project area being assessed must be awarded no marks for that area.

Marking criteria

Analysis (9 marks), documented design (12 marks), technical solution (42 marks), completeness of solution (15 marks), techniques used (27 marks).

Select the band, 1, 2 or 3 with level of demand description that best matches the techniques and skill that the student’s program attempts to cover. The emphasis is on what the student has actually achieved that demonstrates proficiency at this level rather than what the student has set out to use and do but failed to demonstrate, eg because of poor execution. Check the proficiency demonstrated in the program. If the student fails to demonstrate proficiency at the initial level of choice, drop down a level to see if what the student has done demonstrates proficiency at this level for the lower demand until a match is obtained. Table 1 is indicative of the standard required and is not to be treated as just a list of things for students to select from and to be automatically credited for including in their work.

As indicated above, having selected the appropriate level for techniques used and proficiency in their use, the exact mark to award should be determined based upon:

• the extent to which the criteria for the mark band have been achieved
• the quality of the coding style that the student has demonstrated (see Table 2 for exemplification of what is expected)
• the effectiveness of the solution.

Example technical skills

Table 1: example technical skills.

Note that the contents of Table 1 are examples, selected to illustrate the level of demand of the technical skills that would be expected to be demonstrated in each group. The use of alternative algorithms and data models is encouraged. If a project cannot easily be marked against Table 1 (for example, a project with a considerable hardware component) then please consult your AQA non-exam assessment Adviser or provide a full explanation of how you have arrived at the mark for this section when submitting work for moderation.

Table 2: Coding styles

The descriptions in Table 2 are cumulative, ie for a program to be classified as excellent it would be expected to exhibit the characteristics listed as excellent, good and basic not just those listed as excellent.

Testing (8 marks)

Evidence for the testing section may be produced after the system has been fully coded or during the coding process. It is expected that tests will either be planned in a test plan or that the tests will be fully explained alongside the evidence for them. Only carefully selected representative samples are required.

Evaluation (4 marks)

Project tasks that are not of a-level standard.

If the task (problem or investigation) selected for a project is not of A-level standard, mark the project against the criteria given, but adjust, the mark awarded downwards by two marking levels (two marks in the case of evaluation) in each section for all but the technical solution. You should have already taken the standard into account for this, by directly applying the criteria. For example, if a student had produced a 'fully or nearly fully articulated design of a real problem describing how solution is to be structured/is structured'. This would, for an A-level standard project, achieve a mark in Level Four for Documented Design (10-12 marks). If the problem selected was too simple to be of A-level standard but the same criteria had been fulfilled, shift the mark awarded down by two levels, into Level Two, an award of 4-6 marks. If a downward shift by two levels is not possible, then a mark in the lowest level should be awarded.

Guide to non-exam assessment documentation

Students are expected to:

• produce a clear statement that describes the problem area and specific problem that is being solved/investigated
• outline how they researched the problem
• state for whom the problem is being solved/investigated
• provide background in sufficient detail for a third party to understand the problem being solved/investigated
• produce a numbered list of measurable, "appropriate" specific objectives, covering all required functionality of the solution or areas of investigation (Appropriate means that the specific objectives are single purpose and at a level of detail that is without ambiguity.)
• report any modelling of the problem that will inform the Design stage, for example a graph/network model of Facebook connections or an E-R model.

A fully scoped analysis is one that has:

• researched the problem thoroughly
• has clearly defined the problem being solved/investigated
• omitted nothing that is relevant to subsequent stages
• statements of objectives which clearly and unambiguously identify the scope of the project
• modelled the problem for the Design stage where this is possible and necessary.

Students are expected to articulate their design in a manner appropriate to the task and with sufficient clarity for a third party to understand how the key aspects of the solution/investigation are structured and on what the design will rely, eg use of numerical and scientific package libraries, data visualisation package library, particular relational database and/or web design framework. The emphasis is on communicating the design; therefore it is acceptable to provide a description of the design in a combination of diagrams and prose as appropriate, as well as a description of algorithms, SQL, data structures, database relations as appropriate, and using relevant technical description languages, such as pseudo-code. Where design of a user interface is relevant, screen shots of actual screens are acceptable.

Technical solution

Students should provide program listing(s) that demostrate their technical skill. The program listing(s) should be appropriately annotated and self-documenting (an approach that uses meaningful identifiers, with well structured code that minimises instances where program comments are necessary).

Students should present their work in a way that will enable a third party to discern the quality and purpose of the coding. This could take the form of:

• an overview guide which amongst other things includes the names of entities such as executables, data filenames/urls, database names, pathnames so that a third party can, if they so desire, run the solution/investigation
• explanations of particularly difficult-to-understand code sections; a careful division of the presentation of the code listing into appropriately labelled sections to make navigation as easy as possible for a third party reading the code listing.

Students must provide and present in a structured way for example in tabular form, clear evidence of testing. This should take the form of carefully selected and representative samples, which demonstrate the robustness of the complete, or nearly complete, solution/thoroughness of investigation and which demonstrate that the requirements of the solution/investigation have been achieved. The emphasis should be on producing a representative sample in a balanced way and not on recording every possible test and test outcome. Students should explain the tests carried out alongside the evidence for them. This could take the form of:

• an introduction and overview
• the test performed
• its purpose if not self-evident
• the test data
• the expected test outcome
• the actual outcome with a sample of the evidence, for example screen shots of before and after the test, etc, sampled in order to limit volume.

Students should consider and assess how well the outcome meets its requirements. Students should obtain independent feedback on how well the outcome meets its requirements and discuss this feedback. Some of this feedback could be generated during prototyping. If so, this feedback, and how/why it was taken account must be presented and referenced so it can be found easily.

Students should also consider and discuss how the outcome could be improved more realistically if the problem/investigation were to be revisited.

Assessment objective breakdown for non-exam assessment

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A Level Computer Science

What Board do we do?  AQA, AS/A Level code: AS (7516) A Level (7517)

The new AS and A Levels in Computer Science are now "standalone" qualifications. Marks gained at AS Level do not contribute to the final grade at A Level.

What is Computer Science? Computer Science is a discipline which requires thinking both in abstract and in concrete terms. On a higher level, computer science is concerned with problem-solving: modelling and analysing problems, designing solutions, and implementing them. Problem-solving requires precision, creativity, and careful reasoning.

In AS and A Level Computer Science, students learn the principles of computation and algorithms, computer programming, machine data representation, computer systems (hardware and software), computer organisation and architecture, communications and networking, databases and the consequences of using computing. The syllabus is taught in Python.

Which subjects combine well with Computer Science?  Computer Science has strong connections to many other disciplines. Mathematics , Further Mathematics ,  Physics , and Economics combine well with Computer Science. 

Students who wish to study for a Computer Science degree should combine it with A Level Mathematics as this is a prerequisite at many universities.

What can Computer Science lead to?  A good grade in Computer Science at A Level is valued by universities and employers since it requires the development of analytical thinking and problem solving skills. This course also lays an appropriate foundation for further study of Computer Science, Engineering, Physics or related subjects in higher education. Many problems in the sciences, engineering, health care, business and other areas can be solved effectively with computers, but finding a solution requires both computer science expertise and knowledge of the particular application domain. Thus, computer scientists often become proficient in other subjects. 

AS Level AS Paper 1 on-screen exam: 50% of the marks

Students answer a series of short questions and write/adapt/extend programs in an electronic answer document. This paper tests a student's programming ability, and theoretical knowledge of data structures, systematic problem solving, and the theory of computation.

AS Paper 2 written exam: 50% of the marks

This paper tests the fundamentals of data representation, computer systems (hardware and software), computer architecture and organisation, communications and networking, and the consequences of using computing.

A Level A Level Paper 1 on-screen exam: 40% of the marks

Students answer a series of short questions and write/adapt/extend programs in an electronic answer document. This paper is in Python. This paper tests a student's programming ability, and theoretical knowledge of data structures, systematic problem solving, and the theory of computation.

A Level Paper 2 written exam: 40% of the marks

This paper tests the fundamentals of data representation, computer systems (hardware and software), computer architecture and organisation, communications and networking, the consequences of using computing, databases and big data, and functional programming.

Non exam assessment: 20% of the marks

This coursework unit assesses students’ ability to use the knowledge and skills gained through the course to solve or investigate a practical problem.

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A Level Computer Science Course CAIE

Enrolment Fee

 Add ALEVEL10 at checkout for 10% Discount off Multiple A Level courses

Up to 2 years

Up to 56 points

Qualification

Assessments

This A Level Computer Science Course will provide you with a general understanding and perspective of the development of computer technology and systems, which will inform your decisions and support your participation in an increasingly technological dependent society.

This course will develop your knowledge and understanding of computer science through entry to higher education and also provide you with the necessary skills and knowledge to seek employment in areas that use computer science.

Please note that as the awarding body is CAIE, the qualification will be International A’ Level / AS Level Computer Science.

What can you do with an A Level in Computer Science?

The skills you gain from A’ Level Computer Science will allow you to go into Industries as diverse as consultancies, IT service providers, telecommunications, aerospace and defence, financial services, retail, healthcare, manufacturing, agricultural, public and third sectors. Small to medium-sized enterprises (SMEs) also have a range of computing opportunities. It is also possible to set up your own business providing IT services such as web design and consultancy.

If you specialise in computer sicence at higher education, jobs directly related to your degree include:

• Application analyst • Business analyst • Data analyst • Database administrator • Games developer • Information systems manager • IT consultant • Multimedia programmer • SEO specialist • Systems analyst • Systems developer

Previous Knowledge Required

There are no previous entry requirements for this course, however students are expected to have a reasonable standard of literacy. 

You have the freedom to start the course at any time and continue your studies at your own pace for a period of up to 24 months from initial registration with the full support of your Tutor.

The Full A Level has 20 chapters you will need to cover which is split into IAS and IA2.  The IAS Level has 12 modules and all of these are listed below.

Awarding Body: Cambridge

Specification code: 9618, ias modules.

• Data Representation
• Multimedia – Graphics, Sound
• Compression
• Networks including the internet
• Computers and their components
• Logic Gates and Logic Circuits
• Central Processing Unit (CPU) Architecture
• Assembly Language
• Bit manipulation
• perating System
• Language Translators
• Data Security
• Data Integrity
• Ethics and Ownership
• Database Concepts
• Database Management System (DBMS)
• Data Definition Language (DDL) and Data Manipulation Language (DML)
• Computational Thinking Skills
• Data Types and Records
• Introduction to Abstract Data Types (ADT)
• Programming Basics
• Structured Programming
• Program Development Lifecycle
• Program Design
• Program Testing and maintenance

IA2 Modules

• User-defined data types
• File organisation and access
• Floating-point numbers, representation and manipulation
• Circuit switching, packet switching
• Procossers, Parallel Processing and Virtual Machines
• Boolean Algebra and Logic Circuits
• Purposes of an Operating System (OS)
• Translation Software
• Encryption, Encryption Protocols and Digital certificates
• Artificial Intelligence
• Programming Paradigms
• File Processing and Exception Handling

Students will be required to arrange and pay for their examinations / practicals at a CAIE approved centre. We can provide an extensive list of these centres for you.

A Level Exams There are four exams for the full A Level qualification. The length of each exam is as follows:

• Paper 1 – 1 hour 30 min
• Paper 2 – 2 hours
• Paper 3 – 1 hour 30 min
• Paper 4 – 2 hours 30 min (Practical)

AS Level Exams There are two exams for the AS Level qualification. The length of each exam is as follows:

For Cambridge International AS & A Level Computer Science, learners can:

• take Papers 1 and 2 only (for the Cambridge International AS Level qualification) or
• follow a staged assessment route by taking Papers 1 and 2 (for the Cambridge International AS Level qualification) in one series, then Papers 3 and 4 (for the Cambridge International A Level qualification) in a later series or
• take Papers 1, 2, 3 and 4 in the same examination series, leading to the full Cambridge International A Level.

Please note: paper 4 is a practical examination. The programming tasks will be based around a small number of scenarios, learners will be assessed on their ability to write programs or program elements to solve tasks. The centre where you sit your exams must ensure that you have access to a computer that belongs to the centre and it must not have internet access or access to email.

Candidates will be required to use either Java (console mode), Visual Basic* (console mode) or Python (console mode) programming languages.  For this course, we will teach you Python.

A Level Computer Science Online Course Outcome

On successful completion of all your exams for the A Level Computer Science Online Course, you will be awarded one of the following qualifications:

International A Level in Computer Science with CAIE | International AS Level in Computer Science with CAIE

For more information on CAIE, please  click here.

Find an Exam Centre

International gcse, request a prospectus, enrolment fees.

Our Enrolment fee for this course is noted at the top of this page where you can enrol directly onto the course.  This fee includes access to your course including tutor support for 2 years.

Our enrolment fee includes:

• All study materials covering the full specification.
• Full support where you can also message your tutor as many times as you need to.
• Access to our online Library with a full range of eBooks.
• Help completing university applications including UCAS and The Common Application.
• Reference and predicted grade for University.
• Assignment marking and feedback
• Marked and graded practise examination papers
• Eligibility for a Totum Card if you reside within the UK
• Fast Track A Level if required and flexible learning from home 24/7.

The only other fee you will need to pay is for your exams which is due approximately six months prior and this will be paid directly to the exam centre.

You can enrol online right now by Card or PayPal (Visa, Mastercard, Maestro and American Express). Alternatively, we also accept BACS transfer or we can send you a payment link.

Your A Level course will be online.  You will access it via our online portal.  

With our courses, we have learners from all over the world enrolled.  Therefore, if we restricted your learning to certain times, not everyone would be available.  All our courses are accessible 24/7 via our online secure portal.  Any videos on your portal would be pre-recorded meaning you can work through your course at your own pace.

By opting for our International A Level, you can study the course from anywhere and exam centres are located all over the world.  With our UK A Levels (AQA), you can study them from outside of the UK, however you would need to sit the actual exams for these within the UK.

You will be provided with eBooks for this course. If you want to purchase physical books in addition, then we can provide you with the book ISBN numbers.

The Guided learning hours for A Levels are as follows:-

AS Level: 180 hours

A Level:  360 hours

These figures are for guidance only. The number of hours needed to gain the qualification may vary depending on your previous experience of the subject.

Yes you will gain UCAS points and these depend on your final grade once you have completed your exams. 

If you are referring to A Levels at college then yes!

You will sit the same exam as thousands of students across the world in an exam centre, and achieve the same qualification as everyone else.

Provided you have completed enough work on the course within a reasonable amount of time, we will be able to provide a predicted grade / reference for university. 

Please provide at least 3 months notice for this, otherwise this will incur a small fee.

We want exams to be as competitively priced for our learners as possible and therefore that is why we direct them to the examination centres rather than charge upfront fees.

Still unsure? See below for more information on A Level Computer Science

Did you know that the first mechanical computer – The Babbage Difference Engine, was created in 1822, and weighed over 700 pounds, which is unbelievable when you take into account that the smallest computer in the world can literally fit on a single grain of rice.

Today the use of computers has fully altered our daily lives, from listening to music and internet banking to our world’s hospital and banks. Who would have thought we would be able to do our shopping, listen to music, take high quality photos or even just find directions using our mobile phone? Amazing isn’t it.

You may wonder if you can carve a career in say computer programming, and this is all down to your drive and determination. There are many lucrative positions available that involve computer science and which pathway you decide to take is entirely up to you.

As an example, Mark Zuckerberg, founder of Facebook started learning how to use a computer at 10 years old. By the time he was 11, he was learning programming and built a programme which connected his father’s home computer to his office computer called ‘ZuckNet’. From there he progressed to making games and a programme that learns your music taste; turning down millions of dollars of offers along the way, from the likes of Microsoft in the process.  Because he stayed focused, many other programmes were developed before he finally opened up Facebook to the general public and this currently has in excess of 2.9 billion active users per month.

An essential part of computer science is maths and you may find it useful to run A Level Mathematics alongside this subject as this will help you with the programming concepts. If you find you are not ready to start at A Level standard, you could also consider studying IGCSE Computer Science , which forms a natural progression onto A Level.

Fill in the form below or call us on 0800 160 1556, and we’ll get back to you as soon as we can. Also don’t forget to let us know which course it is that you are interested in…

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AQA CS A level prep. for 2024 paper 1

Subject: Computing

Age range: 16+

Resource type: Assessment and revision

Last updated

1 April 2024

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AQA Computer Science A level Preparation for 2024 paper 1 Contains preparation material for the 2024 Symbol Puzzle pre-release code. It includes an investigation of the code, along with questions, mock exam paper and mark scheme for Python

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Bachelor of Science in Computer Science

• Programs & Majors
• Computer Science BS

Undergraduate

Bachelor of science in computer science (bs), college of science, technology engineering and mathematics, on campus, online, hybrid.

Technology is becoming part of every aspect of our lives, and that role is growing every day. It’s why in the next decade, computer scientist employment is projected to grow by 22%, far outpacing the economy as a whole.

Come to Alabama State University to pursue a computer science bachelor degree and be part of this bright future.

Why Study Computer Science at Alabama State University?

Our computer science graduates work at Fortune 500 companies and government agencies, and as ambassadors for education around the world. Your experience at Alabama State University will prepare you for wherever you go to work:

Seasoned faculty:

Our faculty come from a variety of research backgrounds, including machine learning, artificial intelligence and cybersecurity.

Land your dream job:

Between your faculty advisor and the career workshops we host every semester, we work hard to find you a job when your time at Alabama State is done.

State-of-the-art labs:

Our cybersecurity laboratory and training facility will give you hands-on experience in one of the most in-demand fields today during your time at ASU.

Explore Computer Science Bachelor Degree Courses at ASU

While studying computer science at Alabama State University, you can conduct software engineering projects and work with professors in machine learning:

Introduction to Computer Science:

This course will give you a solid base in the field of computer science, with a specific focus on the technique of algorithm development and programming style.

Programming Concepts, Standards and Methods:

Learn structured programming concepts, problem-solving, algorithm development, coding, debugging, testing and documenting programs in modern high-level computer languages like Python, HTML and Java.

Introduction to Data Structures and Algorithms:

Building on what you learned in Programming Concepts, Standards and Methods, you focus on modules and information biding, data abstraction through classes, structures and unions, recursion, pointers and dynamic data, and linked lists. The course also focuses on object-orienting programming, algorithm analysis, searching, sorting and trees.

Learn more about our courses via the links below:

What Can You Do With a Computer Science Bachelor’s Degree?

The future of the industry looks bright. It is estimated the employment of computer scientists will grow by 22% by 2030, outpacing the average of the economy as a whole. And the median salary for a computer scientist in 2021 was $131,490, according to the U.S. Bureau of Labor Statistics, more than double the average annual household income reported by the U.S. Census.

Our computer science graduates go on to work as programmers, network administrators, designers and security analysts.

When you finish your computer science bachelor’s degree at Alabama State University, you graduate with the ability to critically assess information and logically determine solutions. Employers tell us our graduates see the nuances of a given situation and analyze problems with considerable detail. Their ability to translate a problem into code and find solutions is applicable to a myriad of professional settings.

Places Alumni Work

Why Study Computer Science?

Our program takes a traditional approach to computer science education while also offering opportunities to prepare you for graduate school or to climb the ladder in your chosen career path:

Learn from experienced faculty who care.

Our professors are proven researchers in the field and excellent teachers. They will work hard to make sure you succeed at ASU and beyond.

Close to the action.

Montgomery is in the middle of the Southeast, fewer than 200 miles from Mobile, Birmingham and Atlanta, so you will have countless opportunities to work, intern and network.

Hands-on experience.

You will conduct software engineering projects, work with professors in machine learning exercises and have access to our cybersecurity laboratory and training facility.

Program Callouts

The average size of a computer science class is 30 students or fewer

The median salary of a computer scientist in 2021, according to the U.S. Bureau of Labor Statistics

The projected percent growth expected in the computer science industry in the next decade

Average number of years it takes a student to complete their computer science bachelor of science degree

What Our Computer Science Alumni Say

  “The program was a great experience for me. Prior to actually attending I did have some reservations, but I can say it turned out it be one of the best decisions I have made and is the one of the biggest reasons I am in the position that I am today. The faculty and staff were always readily available and supportive of any needs I may have had. I felt that they actually cared about me as a student and a person. The individual lessons and courses I took were useful and informative. The classes were coherent and clear, and I feel I was able to gain a lot from them. I am now working in my field and can’t be thankful enough for the experience, skills and information I’ve gained from being a part of the program. I can confidently say that this program has prepared me to not only be a working professional in the field of computer science but also to excel as a professional and a person.” Cedric C. ’22, C.S.C BS

Related Programs and Additional Resources

Connect with asu, department of mathematics & computer science.

Still unsure if the computer science program at Alabama State University is right for you? Contact us to find out more!

Michelle J. Foster, Ph.D.

Alabama State University 915 S. Jackson Street Montgomery, AL 36104

(334) 229-4800

FACULTY, STAFF & STUDENT RESOURCES

Alabama State University is accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) to award baccalaureate, master's and doctoral degrees. Alabama State University also may offer credentials such as certificates and diplomas at approved degree levels. Questions about the accreditation of Alabama State University may be directed in writing to the Southern Association of Colleges and Schools Commission on Colleges at 1866 Southern Lane, Decatur, GA 30033-4097, by calling 404.679.4500 , or by using information available on SACSCOC's website. ( www.sacscoc.org ).

To inquire about Alabama State University accreditation status, please contact Dr. Tanjula Petty

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UNITE Fall 2024 Course Offerings

UNITE Distributed Learning provides access to live streaming video of class sessions plus same-day access to streaming video archives and downloadable video and audio files of course meetings to the students who enroll through UNITE, "piggybacking" on an on-campus section of the course in a UNITE-enhanced classroom.

Semester Schedule

The UNITE sections of a course follow the same semester schedule as the on-campus section of the course. This includes exams (which may be required synchronous events - see below) and homework deadlines as well as University deadlines for adding courses, cancelling courses, refunds, etc.

Exams, Presentations and Homework

Assessments (exams, presentations, homework, etc.) vary class-to-class, instructor-to-instructor.  Note that some courses require that exams be taken at the same time/same day as the on-campus section of the course upon which UNITE is "piggybacking" for UNITE-enrolled students as well as live student presentations to the class.

Courses Exams Requiring Synchronous, Live Proctoring

For courses in which the instructor is holding in-class, proctored exams for those enrolled in the on-campus sections, students enrolled through UNITE are REQUIRED  to take exams on the same day/same time as the students enrolled in the on-campus sections of the course with a UNITE-approved proctor.

Any deviation from the same day/same time proctored exams for these courses - including the request to take the exams with the on-campus students - must be approved by the instructor.  UNITE will NOT grant these permissions. Work out these arrangements with the instructor before the 100% refund period ends.  

Students who arrange to come to campus and take in-class, proctored exams with the students enrolled in the on-campus section of a course do not need to find/submit a local proctor - note that this must be arranged with the instructor to verify permission/space (enrollment in a UNITE section does not hold a physical classroom seat in the classroom).

Students are responsible for finding and submitting proctor information to UNITE to evaluate and approve. UNITE will contact all students enrolled through UNITE to initiate this process shortly after the semester begins.

Final Exams: Final exam dates are posted in the official University of Minnesota Class Schedule.  UNITE will stream video on Saturdays. If you are enrolled in a UNITE section with an exam on a Saturday, you will need to have a proctor administer the exam. If you need to make other arrangements you will need to contact the instructor directly to seek approval.

Courses with Exams Not Requiring Live, In-Person Proctoring

For courses for which the instructors are using other types of exams - take-home exams, online exams (with a video proctoring service or without) -  instead of in-class, proctored exams, there is no need for students who enroll in the UNITE section of a course to find and submit a proctor to UNITE for approval.

Presentations

For courses with required live presentations by students - individually or as a group - UNITE will work with the student(s) and instructor to provide a live webconference between the remote student(s) and the classroom in real time.  In some instances, UNITE-enrolled students are able to join the on-campus students in the classroom to present in person (though that is not required).  For courses with required, live presentations  it is best to note that commitment for the course with the instructor before the 100% refund period ends.  

Homework Submission and Return

Increasing, faculty and TAs are using Canvas course sites for submission and return of homework.

For those faculty and TAs who do not, homework may be submitted to UNITE via email. Our office will record submissions and deliver to instructors and/or TAs for grading. Graded materials will be returned to your University email account when we receive it.

For more information, refer to the "Step Two: Know How UNITE Works" of UNITE Steps to Success .

The courses offered are subject to change. For the summer semester, UNITE will stop recording/streaming a course if there are no students enrolled in that course through UNITE.

Course descriptions taken from the University of Minnesota's Schedule Builder . Courses topics may be revised per instructor. Contact instructor for more detailed and up-to-date information.

Grad 0999 – 51566 Call Number – UNITE students must register online themselves for this status. Graduate students registering for this status must register before the semester begins or they will be charged the normal late registration fees.

Undergraduate students taking classes on campus may enroll in UNITE courses with instructors' permission. Learn more about Undergraduate Credit Enrollment though UNITE .

Please note Important Fall Semester Dates .

Students enrolled in on-campus sections have limited access to UNITE Media; refer to UNITE Streaming Video Access for On-Campus Students for more details.

FALL SCHEDULE

(Updated April 2nd, 2024)

Use online tools to search all University credit offerings:  Aerospace Engineering's Class Schedules by Department online search tool  Humphrey School of Public Affairs' ClassInfo online search tool  (Note: These tools list ALL offerings - on-campus, including UNITE offerings)

AEROSPACE ENGINEERING

AEM 5321 (also offered as EE 5231) - Linear Systems and Optimal Control (3.0 cr)   Instructor TBA UNITE streams live video of on-campus section on MW 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [EE 3015, CSE grad student] or instr consent  Description:   Properties and modeling of linear systems. Linear quadratic and linear-quadratic-Gaussian regulators. Maximum principle.

AEM 5401 - Intermediate Dynamics (3.0 cr)   Yohannes Ketema   UNITE streams live video of on-campus section on MWF 11:15 a.m.–12:05 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE upper div or grad, 2012, Math 2243  Description:   Three-dimensional Newtonian mechanics, kinematics of rigid bodies, dynamics of rigid bodies, generalized coordinates, holonomic constraints, Lagrange equations, applications.

AEM 5451 (also offered as EE 5251) - Optimal Filtering and Estimation (3.0 cr)   Demoz Gerbe-Egziabher UNITE streams live video of on-campus section on TTh 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [[MATH 2243, STAT 3021] or equiv], CSE grad student] or dept consent; EE 3025, EE 4231 recommended  Description:   Basic probability theory, stochastic processes. Gauss-Markov model. Batch/recursive least squares estimation. Filtering of linear/nonlinear systems. Continuous-time Kalman-Bucy filter. Unscented Kalman filter, particle filters. Applications.

BIOMEDICAL ENGINEERING

BMEN 5001 - Advanced Biomaterials (3.0)  Wei Shen   UNITE streams live video of on-campus section on TTh 11:15 a.m. - 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   3301 or MatS 3011 or grad student or instr consent   Description:   Commonly used biomaterials. Chemical/physical aspects. Practical examples from such areas as cardiovascular/orthopedic applications, drug delivery, and cell encapsulation. Methods used for chemical analysis and for physical characterization of biomaterials. Effect of additives, stabilizers, processing conditions, and sterilization methods.

BMEN 5401 - Advanced Biomedical Imaging (3.0 cr)   Alexander Opitz UNITE streams live video of on-campus section on TTh 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE upper div or grad student or instr consent Description:   Functional biomedical imaging modalities. Principles/applications of technologies that offer high spatial/temporal resolution. Bioelectromagnetic and magnetic resonance imaging. Other modalities.

BMEN 5411 - Neural Engineering (3.0 cr)   Tay Netoff UNITE streams live video of on-campus section on TTh 11:15 a.m. - 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   BMEN 3401 recommended  Description:   Theoretical basis. Signal processing techniques. Modeling of nervous system, its response to stimulation. Electrode design, neural modeling, cochlear implants, deep brain stimulation. Prosthetic limbs, micturition control, prosthetic vision. Brain machine interface, seizure prediction, optical imaging of nervous system, place cell recordings in hippocampus.

BMEN 5910 - Special Topics in Biomedical Engineering: Biomedical Science Data (3.0 cr)   Matthew Johnson   UNITE streams live video of on-campus section on MW 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE student, upper div or grad  Description:   Description coming from department.

BMEN 8001 - Polymeric Biomaterials (3.0 cr)   Chun Wang UNITE streams live video of on-campus section on MW 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [5001, [CHEN 4214 or MATS 4214 or equiv]] or instr consent Description:   Introduction to polymeric biomaterial research. Molecular engineering, characterization of properties, material-cell interaction, biocompatibility/bioactivity. Applications in biology and medicine.

BMEN 8601 - Biomedical Engineering Seminar (1.0 cr)   Seminars and Colloquia taken for credit are offered only as live and archived streaming video - NO downloadable video or audio podcast versions are offered.   Wei Shen   UNITE streams live video of on-campus section on MW 3:35 p.m. - 4:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Description:   Lectures and demonstrations of university and industry research introducing students and faculty to methods and goals of biomedical engineering.  For more information, see the Biomedical Engineering Graduate Seminar Web Site .

Looking for a course not listed here? Ask for it! We already offer many College of Science and Engineering courses through UNITE, but are looking for other courses that we can offer through UNITE.  Use our online  Course Request Form . 

NOTE: UNITE WILL NOT TAKE REQUESTS FOR ADDITIONAL COURSES FOR FALL 2024 AFTER AUGUST 1ST, 2024.

COMPUTER SCIENCE AND ENGINEERING

CSCI 5106 - Programming Languages (3.0)  UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on TTh 1:00 p.m.–2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   4011 or instr consent  Description:   Design and implementation of high-level languages. Course has two parts: (1) language design principles, concepts, constructs; (2) language paradigms, applications. Note: course does not teach how to program in specific languages.

CSCI 5204 (also offered as EE 5364) - Advanced Computer Architecture (3.0 cr)   UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on TTh 9:45 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   4203 or EE 4363; Credit will not be granted if credit has been received forEE 5364  Description:   Instruction set architecture, processor microarchitecture, memory, I/O systems. Interactions between computer software and hardware. Methodologies of computer design.

CSCI 5421 - Advanced Algorithms and Data Structures (3.0 cr)   UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on MW 8:15 a.m. - 9:30 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSCI 4041 or instr consent  Description:   Fundamental paradigms of algorithm and data structure design. Divide-and-conquer, dynamic programming, greedy method, graph algorithms, amortization, priority queues and variants, search structures, disjoint-set structures. Theoretical underpinnings. Examples from various problem domains.

CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming (3.0 cr)   UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on MW 8:15 a.m. - 9:30 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   4041 or instr consent  Description:   Parallel architectures design, embeddings, routing. Examples of parallel computers. Fundamental communication operations. Performance metrics. Parallel algorithms for sorting. Matrix problems, graph problems, dynamic load balancing, types of parallelisms. Parallel programming paradigms. Message passing programming in MPI. Shared-address space programming in openMP or threads.

Looking for a course not listed here? Ask for it! We already offer many College of Science and Engineering courses through UNITE, but are looking for other courses that we can offer through UNITE.  Use our online  Course Request Form .    NOTE: UNITE WILL NOT TAKE REQUESTS FOR ADDITIONAL COURSES FOR FALL 2024 AFTER AUGUST 1ST, 2024.

CSCI 5481 - Computational Techniques for Genomics (3.0 cr)   UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on MW 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSCI 4041 or instr consent  Description:   Techniques to analyze biological data generated by genome sequencing, proteomics, cell-wide measurements of gene expression changes. Algorithms for single/multiple sequence alignments/assembly. Search algorithms for sequence databases, phylogenetic tree construction algorithms. Algorithms for gene/promoter and protein structure prediction. Data mining for micro array expression analysis. Reverse engineering of regulatory networks.

CSCI 5525 - Machine Learning (3.0 cr)   UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on TTh 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Grad student or instr consent  Description:   Models of learning. Supervised algorithms such as perceptrons, logistic regression, and large margin methods (SVMs, boosting). Hypothesis evaluation. Learning theory. Online algorithms such as winnow and weighted majority. Unsupervised algorithms, dimensionality reduction, spectral methods. Graphical models.

CSCI 5541 - Natural Language Processing (3.0 cr)    UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on TTh 11:15 a.m.– 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSCI 2041  Description:   Computers are poor conversationalists, despite decades of attempts to change that fact. This course will provide an overview of the computational techniques developed in the attempt to enable computers to interpret and respond appropriately to ideas expressed using natural languages (such as English or French) as opposed to formal languages (such as C++ or Python). Topics in this course will include parsing, semantic analysis, machine translation, dialogue systems, and statistical methods in speech recognition.

CSCI 5707 - Principles of Database Systems (3.0 cr)   UNITE section enrollment limited by department to 10 (8 graduate and 2 undergraduate) Instructor TBA UNITE streams live video of on-campus section on TTh 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   4041 or instr consent], grad student; Credit will not be granted if credit has been received for CSCI 4707 or INET 4707  Description:   Concepts, database architecture, alternative conceptual data models, foundations of data manipulation/analysis, logical data models, database designs, models of database security/integrity, current trends.

CSCI 8115 - Human-Computer Interaction and User Interface Technology (3.0 cr)   UNITE section enrollment limited by department to 10  Instructor TBA UNITE streams live video of on-campus section on MW 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   5115 or instr consent Description:   Current research issues in human-computer interaction, user interface toolkits and frameworks, and related areas. Research techniques, model-based development, gesture-based interfaces, constraint-based programming, event processing models, innovative systems, HCI in multimedia systems.

CSCI 8523 - AI for Earth: Monitoring Changes in the Environment via Deep Learning (3.0) UNITE section enrollment limited by department to 10  Vipin Kumar UNITE streams live video of on-campus section on MW 2:30 p.m.–3:45 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSci 5523, CSci 5521, or equivalent Description:   Advances in machine learning in conjunction with massive amounts of data from Earth observing satellites offer huge potential for improving our understanding of how the Earth's environment and ecosystems have been changing and how they are being impacted by humans actions and changing climate. Deep learning approaches, that have had phenomenal success in the domain of computer vision and language/speech translation, hold promise in dealing with environmental problems. However, due to challenges that are unique to environmental applications, off-the-shelf deep learning techniques developed for related applications such as computer vision often have limited utility. This class will introduce to the students the promise and challenges in using deep learning techniques to analyze complex, multi-scale, spatio-temporal data for monitoring changes in the Earth and its environment on a global scale.

CSCI 8970 (also offered as DSCI 8970) - Computer Science Colloquium (1.0 cr)   UNITE section enrollment limited by department to 10  Seminars and Colloquia taken for credit are offered only as live and archived streaming video - NO downloadable video or audio podcast versions are offered.   Instructor TBA UNITE streams live video of on-campus section on M 11:15 a.m. - 12:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Description:   Recent developments in computer science and related disciplines. Students must attend 13 of the 15 lectures.  For the entire schedule, see the Computer Science & Engineering Colloquia Series Web Site

DATA SCIENCE

DSCI 8970 (also offered as CSCI 8970) - Data Science Colloquium (1.0 cr)   UNITE section enrollment limited by department to 10 Instructor TBA UNITE streams live video of on-campus section on M 11:15 a.m. - 12:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Description:   Recent developments in computer science and related disciplines. Students must attend 13 of the 15 lectures.  For the entire schedule, see the Computer Science & Engineering Colloquia Series Web Site

ELECTRICAL AND COMPUTER ENGINEERING

EE 4389W (also offered as EE 5389) - Introduction to Predictive Learning (3.0 cr)   Vladimir Cherkassky UNITE streams live video of on-campus section on MW 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [3025, ECE student] or STAT 3022; computer programming or MATLAB or similar environment is recommended for ECE students Description:   Empirical inference and statistical learning. Classical statistical framework, model complexity control, Vapnik-Chervonenkis (VC) theoretical framework, philosophical perspective. Nonlinear methods. New types of inference. Application studies.

EE 4541 - Digital Signal Processing (3.0 cr)   Georgios Giannakis   UNITE streams live video of on-campus section on MW 9:45 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:    [3015, 3025] or instr consent  Description:   Review of linear discrete time systems and sampled/digital signals. Fourier analysis, discrete/fast Fourier transforms. Interpolation/decimation. Design of analog, infinite-impulse response, and finite impulse response filters. Quantization effects.

EE 5163 - Semiconductor Properties and Devices I (3.0 cr)   Tony Low   UNITE streams live video of on-campus section on MW 11:15 a.m. - 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:    [3161, 3601, CSE grad student] or dept consent  Description:   Principles/properties of semiconductor devices. Selected topics in semiconductor materials, statistics, and transport. Aspects of transport in p-n junctions, heterojunctions.

EE 5171 - Microelectronic Fabrication (4.0 cr)   Steven Koester   UNITE streams live video of on-campus section on TTh 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE grad student or dept consent  Description:   Fabrication of microelectronic devices. Silicon integrated circuits, GaAs devices. Lithography, oxidation, diffusion. Process integration of various technologies, including CMOS, double poly bipolar, and GaAs MESFET.

EE 5181 - Micro and Nanotechnology by Self Assembly (3.0 cr)   Jeong-Hyun Cho UNITE streams live video of on-campus section on TTh 4:00 p.m. - 4:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   EE 3161, Phys 1302 Description:   Self-assembly process of micro and nano structures for realization of 1-, 2-, 3-dimensional micro- and nano-devices. Micro and nanoscale fabrication by electrostatic, magnetic, surface tension, Capillary, intrinsic and extrinsic forces. Nanoscale lithographic patterning. Devices packaging, Self-healing process.

EE 5231 (also offered as AEM 5321) - Linear Systems and Optimal Control (3.0 cr)   Instructor TBA UNITE streams live video of on-campus section on MW 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [EE 3015, CSE grad student] or instr consent  Description:   Properties and modeling of linear systems. Linear quadratic and linear-quadratic-Gaussian regulators. Maximum principle.

EE 5239 - Introduction to Nonlinear Optimization (3.0)  Mingyi Hong   UNITE streams live video of on-campus section on MW 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [3025, Math 2373, Math 2374, CSE grad student] or dept consent  Description:   Nonlinear optimization. Analytical/computational methods. Constrained optimization methods. Convex analysis, Lagrangian relaxation, non-differentiable optimization, applications in integer programming. Optimality conditions, Lagrange multiplier theory, duality theory. Control, communications, management science applications.

EE 5241 - Optimal Control and Reinforcement Learning (3.0 cr)   Andrew Lamperski   UNITE streams live video of on-campus section on MW 9:45 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE grad student or instructor consent  Description:   A wide variety of control problems such as "walk from home to school via the shortest path" or "maintain a constant temperature" can be modeled using optimization. This course will survey a variety of methods for modeling and solving optimal control problems. In particular, we will cover numerical optimal control, model predictive control, system identification, dynamic programming, and reinforcement learning. Examples from robotics and aerospace systems will be given.

EE 5251 (also offered as AEM 5451) - Optimal Filtering and Estimation (3.0 cr)   Demoz Gerbe-Egziabher UNITE streams live video of on-campus section on TTh 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [[MATH 2243, STAT 3021] or equiv], CSE grad student] or dept consent; EE 3025, EE 4231 recommended  Description:   Basic probability theory, stochastic processes. Gauss-Markov model. Batch/recursive least squares estimation. Filtering of linear/nonlinear systems. Continuous-time Kalman-Bucy filter. Unscented Kalman filter, particle filters. Applications.

EE 5271 - Robot Vision (3.0 cr)   Changhyun Choi   UNITE streams live video of on-campus section on TTh 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [Math 2373 or equivalent; EE 1301 or equivalent basic programming course]  Description:   Modern visual perception for robotics that includes position and orientation, camera model and calibration, feature detection, multiple images, pose estimation, vision-based control, convolutional neural networks, reinforcement learning, deep Q-network, and visuomotor policy learning.

EE 5301 - VLSI Design Automation I (3.0 cr)    Kia Bazargan   UNITE streams live video of on-campus section on TTh 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [2301, CSE grad student] or dept consent  Description:   Basic graph/numerical algorithms. Algorithms for logic/high-level synthesis. Simulation algorithms at logic/circuit level. Physical-design algorithms.

EE 5323 - VSLI Design I (3.0 cr)   Gerald Sobelman This course uses software that is only available to students in CSELabs due to vendor licensing - there is no off-campus software option. Students will need to come to campus to use the software.   UNITE streams live video of on-campus section on MWF 3:35 p.m. - 4:25 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [2301, 3115, CSE grad student] or dept consent  Description:   Combinational static CMOS circuits. Transmission gate networks. Clocking strategies, sequential circuits. CMOS process flows, design rules, structured layout techniques. Dynamic circuits, including Domino CMOS and DCVS. Performance analysis, design optimization, device sizing.

EE 5329 - VLSI Digital Signal Processing Systems (3.0 cr)   Instructor TBA This course uses software that is only available to students in CSELabs due to vendor licensing - there is no off-campus software option. Students will need to come to campus to use the software.   UNITE streams live video of on-campus section on MWF 3:35 p.m. - 4:25 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [[5323 or concurrent registration is required (or allowed) in 5323], CSE grad student] or dept consent   Description:   Programmable architectures for signal/media processing. Data-flow representation. Architecture transformations. Low-power design. Architectures for two's complement/redundant representation, carry-save, and canonic signed digit. Scheduling/allocation for high-level synthesis.

EE 5333 - Analog Integrated Circuit Design   Ramesh Harjani   UNITE streams live video of on-campus section on TTh 8:15 a.m. - 9:30 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [3115, CSE grad student] or dept consent  Description:   Fundamental circuits for analog signal processing. Design issues associated with MOS/BJT devices. Design/testing of circuits. Selected topics (e.g., modeling of basic IC components, design of operational amplifier or comparator or analog sampled-data circuit filter).

EE 5340 - Introduction to Quantum Computing and Physical Basics of Computing (3.0 cr)     Ulya Karpuzcu   UNITE streams live video of on-campus section on MW 9:45 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE grad student; A previous course in computer architecture is suggested but not required.  Description:   Physics of computation will explore how physical principles and limits have been shaping paradigms of computing. A key goal of this course is to understand how (and to what extent) a paradigm shift in computing can help with emerging energy problems. Topics include physical limits of computing, coding and information theoretical foundations, computing with beyond-CMOS devices, reversible computing, quantum computing, stochastic computing.

EE 5351 - Applied Parallel Programming (3.0 cr)   John Sartori    On-campus sections meets MW 1:25 p.m. - 2:40 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [4363 or equivalent], programming experience (C/C++ preferred)  Description:   Parallel programming/architecture. Application development for many-core processors. Computational thinking, types of parallelism, programming models, mapping computations effectively to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, application case studies.

EE 5364 (also offered as CSCI 5204) - Advanced Computer Architecture (3.0 cr)   UNITE section enrollment limited by department to 10  Pen-Chung Yew UNITE streams live video of on-campus section on TTh 9:45 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:    [[4363 or CSci 4203], CSE grad student] or dept consent; Credit will not be granted if credit has been received for: CSCI 5204  Description:   Instruction set architecture, processor microarchitecture. Memory and I/O systems. Interactions between computer software and hardware. Methodologies of computer design.

EE 5389 (also offered as EE 4389W) - Introduction to Predictive Learning (3.0 cr)   Vladimir Cherkassky UNITE streams live video of on-campus section on MW 2:30 p.m. - 3:45 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   EE 3025, STAT 3022 or equivalent; computer programming or MATLAB or similar environment is recommended. Description:   Empirical inference and statistical learning. Classical statistical framework, model complexity control, Vapnik-Chervonenkis (VC) theoretical framework, philosophical perspective. Nonlinear methods. New types of inference. Application studies.

EE 5531 - Probability and Stochastic Processes (3.0 cr)   Soheil Mohajer   UNITE streams live video of on-campus section on MW 11:15 a.m. - 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:    [3025, CSE grad student] or dept consent  Description:   Probability, random variables and random processes. System response to random inputs. Gaussian, Markov and other processes for modeling and engineering applications. Correlation and spectral analysis. Estimation principles. Examples from digital communications and computer networks.

EE 5561 - Image Processing and Applications: From linear filters to artificial intelligence (3.0)  Mehmet Akcakaya   UNITE streams live video of on-campus section on TTh 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:    [4541, 5581, CSE grad student] or instr consent  Description:   Image enhancement, denoising, segmentation, registration, and computational imaging. Sampling, quantization, morphological processing, 2D image transforms, linear filtering, sparsity and compression, statistical modeling, optimization methods, multiresolution techniques, artificial intelligence concepts, neural networks and their applications in classification and regression tasks in image processing. Emphasis is on the principles of image processing. Implementation of algorithms in Matlab/Python and using deep learning frameworks.

EE 5601 - Introduction to RF/Microwave Engineering (3.0 cr)   Rhonda Franklin   UNITE streams live video of on-campus section on MW 1:00 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [EE 3601, CSE grad student] or dept consent  Description:   Fundamentals of EM theory and transmission lines concepts. Transmission lines and network analysis. CAD tool. Lumped circuit component designs. Passive circuit components. Connectivity to central communication theme.

EE 5624 - Optical Electronics (4.0 cr)   James Leger   UNITE streams live video of on-campus section on TTh 2:30 p.m. - 4:10 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [[3601 or Phys 3002], CSE grad student] or dept consent  Description:   Fundamentals of lasers, including propagation of Gaussian beams, optical resonators, and theory of laser oscillation. Polarization optics, electro-optic, acousto-optic modulation, nonlinear optics, phase conjugation.

EE 5653 - Physical Principles of Magnetic Materials (3.0 cr)   Randall Victora   UNITE streams live video of on-campus section on MWF 2:30 p.m. - 3:20 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE grad student or dept consent  Description:   Physics of diamagnetism, paramagnetism, ferromagnetism, antiferromagnetism, ferrimagnetism. Ferromagnetic phenomena. Static/dynamic theory of micromagnetics, magneto-optics, and magnetization dynamics. Magnetic material applications.

EE 5811 - Biological Instrumentation (3.0) Sang-Hyun Oh   UNITE streams live video of on-campus section on TTh 11:15 p.m. - 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:    CSE grad student  Description:   This course will cover the physics and technology of biological instruments. The operating principles of optical, electrical, and mechanical biosensors will be discussed, followed by transport and delivery of biomolecules to the sensors. Techniques to manufacture these sensing devices, along with microfluidic packaging, will be covered. Lectures will be complemented by lab demo sessions to give students hands-on experiences in microfluidic chip fabrication, microscopy, and particle trapping experiments.

EE 5940 - Special Topics in Electrical Engineering I (3.0) Instructor TBA UNITE streams live video of on-campus section on MW 9:45 p.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE student, upper div or grad  Description:   Course description coming from department.

EE 8351 - Design Automation Techniques for Variation-Aware Computer (3.0 cr)   Instructor TBA UNITE streams live video of on-campus section on MW 9:45 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE grad student. Some background in VLSI design and/or design automation is suggested but not required. Such prior exposure will make the experience in the class much more meaningful.  Description:   High-performance chip design can only be performed with the assistance of design automation tools that comprehend the needs of the designer and deliver solutions that can correctly analyze and optimize these systems. The objective of this class is to provide a view of this emerging universe and acquaint students with new research in this area. Specific topics to be covered include 1) Overview of technology trends and emerging systems 2) Variation-aware design and 3) Design automation issues.

EE 8591 - Predictive Learning from Data   Instructor TBA UNITE streams live video of on-campus section on TTh 11:15 a.m. - 12:30 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   CSE grad student or instr consent  Description:   Methods for estimating dependencies from data have been traditionally explored in such diverse fields as: statistics (multivariate regression and classification), engineering (pattern recognition, system identification), computer science (artificial intelligence, machine learning, data mining) and bioinformatics. Recent interest in learning methods is triggered by the widespread use of digital technology and availability of data. Unfortunately, developments in each field are seldom related to other fields. This course is concerned with estimation of predictive data-analytic models that are estimated using past data, but are used for prediction or decision making with new data. This course will first present general conceptual framework for learning predictive models from data, using Vapnik-Chervonenkis (VC) theoretical framework, and then discuss various methods developed in statistics, pattern recognition and machine learning. Course descriptions will emphasize methodological aspects of machine learning, rather than development of new algorithms.

EE 8660 - Magnetics Seminar (1.0 cr)   Seminars and Colloquia taken for credit are offered only as live and archived streaming video - NO downloadable video or audio podcast versions are offered.   Beth Stadler   UNITE streams live video of on-campus section on F 1:25 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Description:   Current literature, individual assignments (no online seminar schedule available to share).

INDUSTRIAL AND SYSTEMS ENGINEERING

IE 3521 - Statistics, Quality and Reliability (4.0 cr)   Instructor TBA UNITE streams live video of on-campus section on TTh 3:35 p.m. - 5:20 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   MATH 1372 or equiv  Description:   Random variables/probability distributions, statistical sampling/measurement, statistical inferencing, confidence intervals, hypothesis testing, single/multivariate regression, design of experiments, statistical quality control, quality management, reliability, maintainability.

IE 5511 - Human Factors and Work Analysis (4.0 cr)    Instructor TBA  UNITE streams live video of on-campus section on TTh 10:10 a.m. - 12:05 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Upper div CSE or grad student; Credit will not be granted if credit has been received for: HUMF 5211, IE 4511 or ME 5211 Description:   Human factors engineering (ergonomics), methods engineering, and work measurement. Human-machine interface: displays, controls, instrument layout, and supervisory control. Anthropometry, work physiology and biomechanics. Work environmental factors: noise, illumination, toxicology. Methods engineering, including operations analysis, motion study, and time standards.

IE 5531 - Engineering Optimization I (4.0 cr)    Instructor TBA  UNITE streams live video of on-campus section on MW 11:15 a.m. - 1:10 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Upper div or grad student or CNR  Description:   Linear programming, simplex method, duality theory, sensitivity analysis, interior point methods, integer programming, branch/bound/dynamic programming. Emphasizes applications in production/logistics, including resource allocation, transportation, facility location, networks/flows, scheduling, production planning.

IE 5532 - Stochastic Models (3.0 cr)   Instructor TBA UNITE streams live video of on-campus section on TTh 10:10 a.m. - 12:05 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Undergraduate probability and statistics. Familiarity with computer programming in a high level language.  Description:   Introduction to stochastic modeling and stochastic processes. Probability review, random variables, discrete- and continuous-time Markov chains, queueing systems, simulation. Applications to industrial and systems engineering including production and inventory control.

IE 8521 - Optimization (4.0 cr)   Instructor TBA UNITE streams live video of on-campus section on TTh 1:25 p.m. - 3:20 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Familiarity with linear algebra and calculus. Description: Theory and applications of linear and nonlinear optimization. Linear optimization: simplex method, convex analysis, interior point method, duality theory. Nonlinear optimization: interior point methods and first-order methods, convergence and complexity analysis. Applications in engineering, economics, and business problems.

IE 8564 - Optimization for Machine Learning (4.0 cr)   Instructor TBA UNITE streams live video of on-campus section on M 2:45 p.m. - 6:05 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Graduate Student Description: Machine learning has been widely used in many areas such as computer vision, search engines, speech recognition, robotics, recommender systems, bioinformatics, social networks, and finance. It has become an important tool in prediction and data analysis. This course provides a comprehensive overview of important optimization models for machine learning. It also systematically provides a theoretical and computational study on various optimization methods for solving these models and more general problems.

MECHANICAL ENGINEERING

ME 5312 -  Solar Thermal Technologies(3.0) Natasha Wright UNITE streams live video of on-campus section on MW 10:10 p.m.–12:05 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   [3333, CSE upper Div] or grad student Description:   Solar radiation fundamentals. Measurement/processing needed to predict solar irradiance dependence on time, location, and orientation. Characteristics of components in solar thermal systems: collectors, heat exchangers, thermal storage. System performance, low-temperature applications. Concentrating solar energy, including solar thermo-chemical processes, to produce hydrogen/solar power systems and photovoltaics. Solar design project.

ME 8446 - Advanced Combustion (3.0) Sayan Biswas UNITE streams live video of on-campus section on TTh 11:15 a.m.–12:05 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   Undergrad courses in thermodynamics, fluid mechanics, heat transfer, IT grad student; 5446 or 8641 highly recommended Description:   Fundamental understanding of linkage between thermodynamics, chemical kinetics, and transport phenomena in combustion systems. Heat release rate, flame stability, and emissions. How those issues arise in furnaces, internal combustion engines, and rockets.  

STAT 5021 - Statistical Analysis (4.0 cr)   Enrollment in STAT 5021 includes on-campus lab in section 2 of the lab sections (T 10:10 a.m. - 11:00 a.m.), live-streamed from a UNITE classroom   Instructor TBA UNITE streams live video of on-campus lecture section on MWF 10:10 a.m. - 11:00 a.m.  UNITE streams live video of on-campus lab section on T 10:10 a.m. - 11:00 a.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   college algebra or instr consent; credit will not be granted if credit has been received for STAT 3011  Description:   Intensive introduction to statistical methods for graduate students needing statistics as a research technique.

STAT 5102 - Theory of Statistics II (4.0 cr)   Enrollment in STAT 5101 includes on-campus lab in section 2 of the lab sections (T 2:30 p.m. - 3:20 p.m.), live-streamed from a UNITE classroom   Instructor TBA UNITE streams live video of on-campus lecture section on MWF 2:30 p.m. - 3:20 p.m.  UNITE streams live video of on-campus lab section on T 2:30 p.m. - 3:20 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   5101 or Math 5651  Description:   Sampling, sufficiency, estimation, test of hypotheses, size/power. Categorical data. Contingency tables. Linear models. Decision theory.

STAT 5302 - Applied Regression Analysis (4.0 cr)   Enrollment in STAT 5302 includes on-campus lab in section 2 of the lab sections (Th 11:15 a.m. - 12:05 p.m.), live-streamed from a UNITE classroom   Instructor TBA UNITE streams live video of on-campus lecture section on MWF 1:25 p.m. - 2:15 p.m.  UNITE streams live video of on-campus lab section on Th 11:15 a.m. - 12:05 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   3032 or 3022 or 4102 or 5021 or 5102 or instr consent Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.  Description:   Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications.

STAT 5421 - Statistical Analysis (3.0 cr)   Instructor TBA UNITE streams live video of on-campus section on MWF 1:25 p.m. - 2:15 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   STAT 3022 or 3032 or 3301 or 5302 or 4051 or 8051 or 5102 or 4102  Description:   Varieties of categorical data, cross-classifications, contingency tables. Tests for independence. Combining 2x2 tables. Multidimensional tables/log linear models. Maximum-likelihood estimation. Tests for goodness of fit. Logistic regression. Generalized linear/multinomial-response models.

STAT 5511 - Time Series Analysis (3.0 cr)   Instructor TBA UNITE streams live video of on-campus section on MWF 2:30 p.m. - 3:20 p.m.  Archived videos typically available to UNITE-enrolled students within an hour  Prerequisites:   STAT 4102 or STAT 5102 Description:   Characteristics of time series. Stationarity. Second-order descriptions, time-domain representation, ARIMA/GARCH models. Frequency domain representation. Univariate/multivariate time series analysis. Periodograms, non parametric spectral estimation. State-space models.

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