Computer Science with Artificial Intelligence MSci/BSc (Hons) with foundation year

In the first year, the curriculum is shared across related courses allowing you to gain a broad grounding in the discipline before going on, in the second and third years, to specialist modules in your chosen field.

The common first year enables you to work alongside students doing similar courses to you, to widen your knowledge and exposure to other subject areas and professions. You will have the opportunity to collaborate with other students, so you can share your insights and experience which will help you to develop and learn.

If you discover an interest in a specific subject you have studied, upon successful completion of your first year, you could swap degrees with another course in your common first year (subject to meeting progression requirements).

Common first-year courses

• Information Technology Management BSc (Hons)
• Interactive Media and Web Technologies BSc (Hons)
• Software Engineering BSc (Hons)

Modules

• Programming: Concepts and Algorithms - 20 Credits

  Whatever software we’re developing, we need to understand the fundamentals of programming to build it – that’s as true for an interactive website as it is for a smart-phone app. In this module, you’ll be introduced to these fundamentals through an accessible and industry-favoured programming language. You’ll explore algorithms – what they are, why they’re important, and how to use them – and you’ll combine this with your programming skills to write your own programs. 

  Compulsory

• Computer Systems - 20 Credits

  To apply, extend or enhance information systems, any developer needs a fundamental understanding of the machine, with all its complex, moving parts. This module introduces you to these concepts, taking them from the concept of computation to the twitching transistors which drive its implementation. 

  CPU architectures, memory hierarchies, efficiency, networking and security are all explored. Additionally, the concept of the Operating System is introduced which, combined with the other topics studied, empowers you to begin your journey as a developer. 

  Compulsory

• Working with Data - 20 Credits

  Databases are fundamental to modern, digital life – whatever we’re doing, we’re either generating, using, sharing or erasing data. The technologies, ethics and laws behind these processes are a fascinating and fundamental element of software development in the 21st century.

  In this module, you’ll explore all these concepts, mastering the elements of data handling, storage, and management which you’ll have to apply in later study. 

  Compulsory

• Mathematical Skills for Computing Professionals - 20 Credits

  Fundamental to all programming is the notion of mathematics. Whenever we write software, we are writing algorithms and algebra – and to write them correctly, we need a firm grip of the maths which underpins them. In this module, you’ll gain that understanding, exploring subjects like set theory, algorithms and complexity, and logical arithmetic.

  Don’t be intimidated, though! Everything is explained from first principles, and you’re supported throughout your mathematical studies by Coventry University’s maths support service. 

  Compulsory

• Programming: Professional Practice - 20 Credits

  This module builds upon and develops the fundamental computer programming skills you developed in Concepts and Algorithms. You will be introduced to new ideas such as object-orientation, and designing reusable code, and you’ll explore them using another industry-favoured programming language. You’ll be taught to structure your code in a way which makes it easy to follow, maintain, and extend, equipping you for the next stage of your software development studies. 

  Compulsory

• Integrative Project Module - 20 Credits

  The Integrative Project module adopts an activity led approach to learning, where you’ll work in a team to plan and execute a project related to your course. The project provides you a vital opportunity to consolidate and apply what you’ve learned during your first year of study, as well as develop new technical and team-working skills.

  You’ll be given a high degree of autonomy during the project, assuming responsibility for all aspects of its conduct. Everything from organising group meetings and distributing tasks and work packets, to reflecting on your progress.

  Compulsory

In Year two, you will develop more advanced knowledge and skills in relation artificial intelligence, theory of computation, software engineering, amongst others. 

Modules

• Artificial Intelligence - 20 Credits

  In this module you’ll aim to gain a comprehensive understanding of modern artificial intelligence concepts and applications. You’ll explore the differing definitions of just what ‘artificial intelligence’ means, and the legal and ethical issues which arise surrounding decision-making computer systems. Ultimately, you’ll seek to build a portfolio of solutions which address artificial intelligence challenges, as you navigate areas such as knowledge representation, reasoning, and how human factors impact the field of AI. 

  Compulsory

• Theory of Computation - 20 Credits

  The Theory of Computation module dives into the mathematical heart of programming. You’ll be guided through some of the more challenging topics in computing such as formalisation of languages, models of computation, and the nature of computability. Ultimately, this module aims to empowers you to assess whether a problem has a computable solution – or one that you can compute before the sun expands to engulf the Earth. 

  Compulsory

• Advanced Algorithms - 20 Credits

  Building on your programming and algorithms studies from first year, this module expands your insights into advanced programming techniques and complex data structures. You’ll learn what terms such as ‘graph’ and ‘tree’ mean in computing, and how to use them in your own software development. You’ll look to become familiar with strategies to address the computational complexity of the problems you’re trying to solve, empowering you to write more sophisticated, and more efficient, software solutions. 

  Compulsory

• Operating Systems, Security, and Networks - 20 Credits

  What is an OS, and what does it do? These two questions are the focus of this module, where you’ll become familiar with the way the operating system you use every day is structured, why it’s structured that way, and how it works. In addition to this, the module introduces the idea of networked computer systems and the accompanying security concepts, exploring topics such as cryptography, user authentication, socket programming and network protocols. 

  Compulsory

• Data Science - 20 Credits

  Picking up where Working with Data left off, the Data Science module equips you with the skills and tools you need to explore the world of Big Data. Using state-of-the-art software, you’ll explore concepts such as predictive modelling, data wrangling, sampling, and analysis. You’ll also explore the complex subject of data visualisation, and how you can use visualisation techniques to make the results of your data analysis understandable to every audience. 

  Compulsory

• Software Engineering - 20 Credits

  Focusing on the professional conduct of software development projects, this module introduces you to several industry-standard practices which underpin effective and efficient software engineering to meet the exacting quality standards. You’ll undertake a real-world software development project, evaluating and selecting the best tools for the task at hand while employing common professional practices such as configuration management and version control. You’ll aim to develop an exhaustively tested, highly polished software deliverable to demonstrate your skills to prospective employers. 

  Compulsory

There’s no better way to find out what you love doing than trying it out for yourself, which is why a work placement² can often be beneficial. Work placements usually occur between your second and final year of study. They’re a great way to help you explore your potential career path and gain valuable work experience, whilst developing transferable skills for the future. 

If you choose to do a work placement year, you will pay a reduced tuition fee³ of £1,250. For more information, please go to the fees and funding section. During this time you will receive guidance from your employer or partner institution, along with your assigned academic mentor who will ensure you have the support you need to complete your placement.  

Modules

• UK Work Placement– 0 credits

  This module² provides you with an opportunity to reflect upon and gain experience for an approved placement undertaken during your programme. A placement should usually be at least 26 weeks or equivalent; however, each placement will be considered on its own merits, having regard to the ability to achieve the learning outcomes. 

  Optional

• International Study/Work Placement – 0 credit

  This module² provides you with an opportunity to reflect upon and gain experience for an approved international study/work placement undertaken during your programme. A work/study placement should usually be at least 26 weeks or equivalent; however, each placement will be considered on its own merits, having regard to the ability to achieve the learning outcomes.

  Optional

In Year three, you will develop more advanced knowledge and skills to do with security, machine learning, group project discovery, amongst others. 

Modules

• Security - 20 Credits

  You’ll first encounter the concept of computer security when you learn about Operating Systems. This module dives into the subject in-depth, as outlined by the British Computer Society’s accreditation criteria. Developed by our Cybersecurity specialists, this module introduces you to the concepts and practical considerations of creating and evaluating secure computer systems. In addition to the technical issues involved, you’ll also explore security legislation and the regulations which apply to associated products and services. 

  Compulsory

• Machine Learning - 20 Credits

  Building on your existing knowledge of Artificial Intelligence, this module dives into the broad field of machine learning, one of the core building blocks of many AI systems and methods. You’ll learn the difference between supervised and unsupervised machine learning, what an artificial neural network is and when best to deploy one to solve a problem, and how to analyse the effectiveness of a wealth of machine learning algorithms when applied to actual data. 

  Compulsory

• Robots and Intelligent Agents - 20 credits

  Modern computing applications often use agents and robots to automate some of their functionality.  The module will explore the ways in which robots and agents are constructed and integrated into advanced distributed systems. The teaching material will cover relevant techniques and will consider examples of the use of robots and agents. 

  Compulsory

• Artificial Neural Networks - 20 credits

  Neural networks are computational models how the human brain works. They have been successfully used in a wide range of applications including image processing, speech and natural language processing, medical diagnosis, bioinformatics, emotion recognition, and robotics. This module provides an introduction to the concepts used in neural networks and their application to solving real-world problems.  

  Compulsory

• Project Discovery - 20 Credits

  In your final year, you will complete a project which is defined and driven by you, bringing your interests and learning together to produce a showcase for your skills. Working with an allocated subject specialist supervisor, the Project Discovery module will equip you with the research and project management skills to define, propose, and start work on a substantial computer science project of your choosing.  

  Compulsory

• Dissertation and Project Artefact - 20 Credits

  Working with an allocated subject expert as supervisor, you will deliver a project dissertation together with a project artefact, usually an advanced piece of software. The Dissertation and Project Artefact module is designed to give you the experience to self-manage project development, evaluation and successful delivery to a self-defined brief, allowing you to produce a substantial piece of work that brings together your learning over the course of the degree. 

  Compulsory

If you meet the criteria, you could choose to take an additional fourth year master's option (subject to additional fees – please refer to the Tuition Fees section for further information), which will deepen your knowledge and expertise. The MSci year aims to consolidate and strengthen the skills you’ve developed over the course of your first three years of study. Building on your existing knowledge, you’ll explore a series of highly advanced subjects in the field of Computer Science with AI which lie beyond the scope of undergraduate study, from Computer Vision to Web Applications and AI, equipping you to undertake employment or postgraduate research at the leading edge of digital technology. 

Modules

• Individual Research Project Preparation - 15 Credits

  In this module, you will identify a topic suited for a substantial piece of research into an area connected to the discipline of computer science. You'll exercise and extend your skills in gathering, understanding and critically evaluating literature; assessing and acting on relevant ethical and legal issues; and applying planning processes for the undertaking of a significant piece of work. This will culminate in the production of a well-structured project plan. 

  Compulsory

• Individual Research Project - 15 Credits

  Building on the literature survey and planning developed as part of the Preparation module, you will undertake the project in this module. Supported by a member of academic staff, you will develop your solution to the chosen challenge, gather primary research data regarding your solution, and document the project's scientific conduct and outputs. 

  Compulsory

• Computer Vision - 15 Credits

  Computer vision (CV) is the field that allows smartphones to identify where to focus an image, or a social media app to identify the face of someone in a photograph. In this module, you’ll be introduced to the models, algorithms and hardware involved in building CV applications from scratch using commonly employed APIs. Crucially, you’ll be taught how to select the right tool for the job, depending on the purpose of the CV problem you’re trying to solve. 

  Compulsory

• Natural Language Processing - 15 credits

  Natural language processing (NLP) makes it possible for computers to recognise, process and respond appropriately to human speech and text. The aim of this module is to give students an understanding of, and ability to use, automated methods for processing text, and to introduce NLP solutions for a wide range of real-world applications on pure text data. 

  Compulsory

• Modelling and Optimisation under Uncertainty - 15 credits

  The main aim of this module is to provide students with more advanced concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning. 

  Compulsory

• Web Applications and AI - 15 credits

  The web is ubiquitous in the contemporary world, and this module is about how web applications can be supported and enhanced using AI techniques, for example to improve customer services or predict and respond to user needs. This module concerns the practical development of AI-enhanced web applications as well as the range of approaches possible.  

  Compulsory

• Information Retrieval - 15 credits

  The web allows modern computer applications to retrieve and interpret information from multiple sources. This module teaches a range of current techniques including web crawlers, query processors, methods for classification, and document analysis.  

  Compulsory

• Big Data Management and Data Visualisation - 15 credits

  Organisations and businesses are being inundated with very large volumes of data - structured and unstructured - daily. This data is too big and complex for processing and analysing using well-known traditional methods. This module aims to introduce you to the current management and visualisation methods for Big Data. Cutting-edge techniques will be taught which should enable you to discover patterns, relationships and associations in big data sets.

  Compulsory