Computer Science and Artificial Intelligence with Year in Industry BSc

You will gain a basic understanding of the fundamental architecture of computers and computer networks.

You’ll learn how the simple building blocks of digital logic can be put together in different ways to build an entire computer.

You’ll also learn how modern computer systems and networks are constructed of hierarchical layers of functionality which build on and abstract the layers below.

You will spend five hours per week in tutorials, lectures and computer classes.

This module considers both the structure of databases, including how to make them fast, efficient and reliable, and the appropriate user interfaces which will make them easy to interact with for users. You will start by looking at how to design a database, gaining an understanding of the standard features that management systems provide and how you can best utilise them, then develop an interactive application to access your database.

Through the lectures and computing sessions you will learn how to design and implement systems using a standard database management system, web technologies and GUI interfaces through practical programming/system examples.

You will gain a broad overview of the fundamental theories and techniques of artificial intelligence (AI).

You’ll explore how computers can produce intelligent behaviour, and will consider topics such as the history of AI, AI search techniques, neural networks, data mining, philosophical and ethical issues, and knowledge representation and reasoning.

You will spend two hours per week in lectures for this module. 

This module focuses on the fact that programming is only one step of the larger Software Engineering Process. To develop good software, you must gather requirements, design it well, plan the development, do the programming, have a testing strategy, test the parts and the product as a whole, and have a maintenance strategy for fixing the things that no one (even the client) imagined were important until it after it was delivered.

Software Engineering is a process that is much more than just programming. You'll spend two-three hours per week discussing the stages of the Software Engineering process in lectures, whilst carrying out activities in labs that help you understand the underlying issues.

You’ll cover the basic concepts in mathematics which are of relevance to the computer scientists.

These include:

• logic
• sets
• functions and relations
• graphs
• induction
• basic probability
• statistics and matrices

The module introduces basic principles of programming and algorithms. It covers fundamental programming constructs, such as types and variables, expressions, control structures, and functions.

You'll learn how to design and analyse simple algorithms and data structures that allow efficient storage and manipulation of data. You'll also become familiar with basic software development methodology.

You will spend around six hours per week in lectures, computer classes and tutorials.

This module runs alongside 'Computer Fundamentals' and provides an expanded view by considering how real computer systems (such as ARM, x86, Linux and *BSD) and networks work.

You’ll also cover the principles of the lower level implementation of I/O using polling and interrupts, and the use of exceptions; how memory and storage are organized as well addressing the issues arising from multicore systems. 

You’ll spend around five hours per week in tutorials, lectures and computer classes.

In this module you will learn the basic principles of the object-oriented and functional approaches to programming, using the languages Java and Haskell. You will also see how they can be used in practice to write a range of different kinds of programs.

This module covers important aspects of algorithms, namely their correctness and efficiency.

You’ll study topics such as:

• proofs in propositional logic and predicate logic
• classical vs. intuitionistic reasoning
• basic operations on types
• verification of list based programs
• introduction to program specification and program correctness

To address the issue of efficiency we cover the use of mathematical descriptions of the computational resources needed to support algorithm design decisions. The emphasis is upon understanding data structures and algorithms so as to be able to design and select them appropriately for solving a given problem.

Working in groups of around five to six people, you’ll be assigned a supervisor who will provide you with a short written description of a computer application to be designed, programmed, and documented during the course of the module.

Each group will meet twice a week, once with your supervisor and once without; you’ll also have four introductory one hour lectures.

This course covers the fundamentals of operating systems and concurrency.

Topics in operating systems include:

• the architecture of operating systems
• process management
• memory management
• file systems
• a brief introduction to virtualisation and cloud computing

The principles of concurrency will be introduced from both the perspective of an operating system. Specific topics on concurrency include:

• hardware support for concurrency
• mutual exclusion
• the use of threads
• synchronisation

You'll investigate classes of formal language and the practical uses of this theory, applying this to a series of abstract machines ultimately leading to a discussion on what computation is and what can and cannot be computed.

You'll focus in particular on language recognition, but will study a range of topics including:

• finite state machines
• regular expressions
• context-free grammars
• Turing machines
• Lambda calculus

This module builds on parts of the ACE module addressing data structures and formal reasoning and introduces concepts which are important to understand the analysis of algorithms in terms of their complexity.

This module builds on the Fundamentals of Artificial Intelligence module. The emphasis is on building on the AI research strengths in the School.

You will be introduced to key topics such as AI techniques, fuzzy logic and planning, and modern search techniques such as Iterated Local Search, Tabu Search, Simulated Annealing, Genetic Algorithms, and Hyper-heuristics, etc.

You will also explore the implementation of some AI techniques.

This module builds on your basic Java programming and software engineering skills developed in year one, extending it to working with larger third-party software systems and the challenges associated with this.

Topic examples include:

• design diagrams and modelling
• GUI programming
• testing software engineering methodologies (including agile development)

All in the context of understanding and refactoring third-party code.

You will spend around two hours per week in lectures, two hours per week in computer classes, and one hour per week in workshops studying for this module.

Building upon the introductory Functional Programming module in year one, you’ll focus on a number of more advanced topics such as: 

• programming with effects
• reasoning about programs
• control flow
• advanced libraries
• improving efficiency
• type systems
• functional pearls

You’ll spend around four hours per week in lectures and computer classes.

You will cover the programming material and concepts necessary to obtain an understanding of the C++ programming language.

You will spend around four hours per week in lectures and computer classes for this module and will be expected to take additional time to practice and to produce your coursework.

This module introduces the field of digital image processing, a fundamental component of digital photography, television, computer graphics and computer vision.

You’ll cover topics including:

• image processing and its applications
• fundamentals of digital images
• digital image processing theory and practice
• applications of image processing

You’ll spend around three hours in lectures and computer classes each week.

An overview of the field of human computer interaction which aims to understand people's interactions with technology and how to apply this knowledge in the design of usable interactive computer systems.

The module will introduce the concept of usability and will examine different design approaches and evaluation methods.

Spending four hours a week in lectures and computer classes, you’ll cover the following topics:

• security of the computer
• security of networks
• security and the internet
• software and hardware security
• mobile security
• basic cryptography

The module covers a range of professional, ethical, social and legal issues in order to study the impact that computer systems have in society and the implications of this from the perspective of the computing profession.

In particular, the module covers topics such as introduction to ethics, critical thinking, professionalism, privacy, intellectual and intangible property, cyber-behaviour, safety, reliability accountability, all these within the context of computer systems development.

Providing you with an introduction to machine learning, pattern recognition, and data mining techniques, this module will enable you to consider both systems which are able to develop their own rules from trial-and-error experience to solve problems, as well as systems that find patterns in data without any supervision. In the latter case, data mining techniques will make the generation of new knowledge possible, including very big data sets. This is now fashionably termed 'big data' science.

You'll cover a range of topics including:

• machine learning foundations
• pattern recognition foundations
• artificial neural networks
• deep learning
• applications of machine learning
• data mining techniques and evaluating hypotheses

You’ll perform an individual project on a topic in computer science with emphasis in artificial intelligence. You’ll produce a 15-25,000 word project report under the guidance of your supervisor, who you will meet with for an hour each week.

The topic can be any area of the subject which is of mutual interest to both the student and supervisor, but should involve a substantial software development component. 

You’ll be given a basic introduction to the analysis and design of intelligent agents, software systems which perceive their environment and act in that environment in pursuit of their goals.

You’ll cover topics including:

• task environments
• reactive, deliberative and hybrid architectures for individual agents
• architectures and coordination mechanisms for multi-agent systems

You will spend around four hours each week in lectures and tutorials for this module.

As part of the assessment of this module you will produce a research paper-style report, and deliver a conference-style presentation.

You'll examine current techniques for the extraction of useful information about a physical situation from individual and sets of images.

You'll cover a range of methods and applications, with particular emphasis being placed on the detection and identification of objects, image segmentation, pose estimation, recovery of three-dimensional shape and analysis of motion.

These problems will be approached with both traditional and modern Computer Vision approaches including Deep Learning.

You will spend five hours per week in lectures, tutorials, and computer classes for this module.

This module examines how knowledge can be represented symbolically and how it can be manipulated in an automated way by reasoning programs.

Some of the topics you’ll cover include:

• first order logic
• resolution
• description logic
• default reasoning
• rule-based systems
• belief networks