Artificial Intelligence and Data Science BSc (Hons)

Course Content

• Course Details

  This degree in artificial intelligence and data science degree will equip you with a range of knowledge and practical skills required to establish your career. They can aid many career paths, such as a machine learning software engineer, solution architect, project manager or AI research scientist. You will learn the fundamentals and applications of data science and machine learning progressively over the course period.

  Year 1

  During your first year of this AI and Data Science programme, you will study common computer science modules which give you the foundation and flexibility to specialise in your second and third years. Additionally, you’ll study a specialised module that is tailored for artificial intelligence and data science programme students.

  Year 2

  In your second year, you will continue your journey with more specialised modules. These include the Introduction to AI, Cloud Computing and Big Data, and Relational Databases along with other computer science modules. You will also complete a group project where you will be a part of a small design team working to produce an innovative and bespoke AI solution to a real-world challenge.

  Year 3

  In your final year of this artificial intelligence and data science degree, you will acquire comprehensive AI skills in advanced modules. These modules include such as Advanced AI and Applications, Natural Language Processing, Modern Databases, and Media Technology. You’ll be able to develop AI applications using computer vision and neural networks and deploy the solutions in the cloud. On the AI and Data Science course you’ll have an opportunity to complete an independent dissertation on a specialist topic of your choice in the field of artificial intelligence.

  UON Computing society & IEEE

  The Computing Society aims to bring together students interested in computing. The society provides insight into the industry by allowing its members  the opportunity to network with potential clients and employers.  Students also have the opportunity to join the world’s largest professional body at discount rates and join the UON IEEE Student Branch. Joining this branch will enable you to get in contact with students from other academic institutes worldwide.

  Please note the modules shown here relate to the academic year 24/25. The modules relating to the academic year 25/26 will be available from June 2025.

  • Stage 1
    • Problem Solving and Programming (20 Credits)
      Module code: CSY1020

      Status: Compulsory
      This purpose of this module is to: introduce students to the skills, principles and concepts necessary to solve problems in computing; to develop essential skills to enable the solution of these problems with the construction of appropriate algorithms and a computer program; introduce principles underlying the design of a high level programming language (HLPL); gain experience and confidence in the use of a HLPL to implement algorithms; implement HLPL programs using an appropriate programming language e.g. Java; introduce an object-oriented language initially as a non-object language.
    • Mathematics for Computer Science (20 Credits)
      Module code: CSY1060

      Status: Compulsory
      This module introduces a set of mathematical topics, which include binary number system, logic circuits, linear systems, graph theory, probability and statistics, that are widely studied by those learning computing sciences. The module equips students with fundamental mathematical skills which underpin a range of computing disciplines.
    • Computer Systems (20 Credits)
      Module code: CSY1061

      Status: Compulsory
      This module provides knowledge of the hardware and software components that make up a computer system and overview the important concepts in preparation for future study of computer science.
    • Computer Communications (20 Credits)
      Module code: CSY1062

      Status: Compulsory
      This module develops student?s understanding of the principles of communication networks and how to classify the various network devices in the appropriate layer of the protocol stack. Students will learn how to manage IP addresses in a small network and will develop confidence in using network simulation software.
    • Web Development (20 Credits)
      Module code: CSY1063

      Status: Compulsory
      This purpose of this module is to give students an understanding of client side web technologies. This module provides students with: the essential knowledge and practical skills to design, develop and implement a Web site to contemporary web standard
    • Software Engineering Fundamentals (20 Credits)
      Module code: CSY1064

      Status: Compulsory
      The purpose of this module is to develop student's experience with the multiple stages of software engineering life-cycles from initial need and requirements identification through to the design and implementation of code in order to develop confidence in the use of terminology and techniques for each of the stages.
  • Stage 2
    • Relational Databases (20 Credits)
      Module code: CSY2080

      Status: Compulsory
      The purpose of this module is to understand and apply the principles of database integrity to implement and utilise efficient databases. RD is a practical module that employs data modelling and SQL techniques to design, define and manipulate data.
    • Cloud Computing and Big Data (20 Credits)
      Module code: CSY2081

      Status: Compulsory
      The purpose of this module is to provide a fundamental understanding of the concepts of big data, virtualisation, and cloud computing. Students explore, select and justify appropriate frameworks/technologies for big data processing, virtualisation, and cloud computing solutions for a given scenario.
    • Introduction to Artificial Intelligence (20 Credits)
      Module code: CSY2082

      Status: Compulsory
      The module introduces fundamentals of data science and machine learning. Students will gain understanding of ethical and legal considerations when analysing data and acquire skills to address bias. Students will practice using data processing, modelling and visualisation tools for problem solving of practical challenges and the development of AI-driven applications
    • Data Structures and Algorithms (20 Credits)
      Module code: CSY2087

      Status: Compulsory
      This module provides students with a conceptual understanding of common data structures and algorithms used in Computer Science and Software Engineering. It enables students to implement and evaluate a selection of algorithms and abstract data types, including linked lists, stacks, queues, graphs and binary trees using an object-oriented language.
    • Group Project (20 Credits)
      Module code: CSY2088

      Status: Compulsory
      The module is designed to develop higher-order intellectual skills (problem-solving) and appropriate personal qualities including team working. Each group will develop and document effective, robust and high-quality computing systems to a professional standard in response to a supplied specification of requirements.
    • Web Programming (20 Credits)
      Module code: CSY2089

      Status: Compulsory
      This purpose of this module is to give students an understanding of the concepts and technologies of web based server side technologies; teach students to use up-to-date programming techniques to design and develop coherent server side software for websites with a focus on security, functionality and usability.
  • Stage 3
    • Natural Language Processing (20 Credits)
      Module code: CSY3055

      Status: Compulsory
      This module introduces the most recent theories, methods, and tools in Natural Language Processing (NLP) to develop high-performance NLP-driven applications. Students apply traditional and advanced NLP methods to common use-cases, with a focus on establishing successful Machine Learning-based NLP solutions using cutting-edge Deep Learning algorithms and Transfer Learning methods.
    • Media Technology (20 Credits)
      Module code: CSY3058

      Status: Compulsory
      Media Technology is an important aspect to Computer Science. This module will introduce a range of technologies relevant to modern multimedia systems. This includes computer graphics, digital image processing, online video streaming, immersive media, and other advanced applications. Student will develop audio-visual systems in a third generation computer language.
    • Modern Databases (20 Credits)
      Module code: CSY3059

      Status: Compulsory
      The purpose of this module is to study advanced/latest database topics. The module focuses primarily on NoSQL databases (e.g., graph and document databases), from designing and creating to querying the databases.
    • Advanced AI and Applications (20 Credits)
      Module code: CSY3060

      Status: Compulsory
      The purpose of this module is to: teach students the fundamental theories and practical applications of advanced artificial intelligence techniques including artificial neural networks, image classification and object detection. The underpinning concepts will be introduced, followed by examples of how responsible and ethical artificial intelligence applications are developed and tested.
    • Computing Project Dissertation (40 Credits)
      Module code: CSY4022

      Status: Compulsory
      This project module provides the opportunity for the student to undertake independent research, development, and self-management of a Computing related project leading to completing a dissertation. An essential outcome for this module is that the student?s project deliverable includes the design and development of a system, or a software application, or a novel functional approach that relates to the main areas of student study, and that can be used, applied or demonstrated in some way. Students on the BSc Business Computing may engage on a research centered project resulting in a report of analysis of an appropriate topic.

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• Student Perks

  At the University of Northampton, everything we do, from funded trips to paid internships, is to give you everything you need to make a difference when you leave.

  If you join this full time Artificial Intelligence and Data Science degree at the University of Northampton, you will receive a laptop when your course begins*. The laptops are built to a bespoke custom specification ideal for use in the seminar room, collaborative group work or studying at home.

  Whatever your ambitions, we’re here to help you to achieve them. We’ll support you to identify the skills you’re learning during your course, find your strengths and secure practical experience so that when it comes to applying for jobs or further study you’ll feel confident in standing out from the crowd. We’ve created the Northampton Employment Promise because we are so confident that if you focus on your studies and complete one of our awards you’ll be highly employable by the time you graduate. Putting you in a great position to secure employment or continue your studies.

  To check out the full list of perks, visit our Student Perks page or dedicated International Perks page.

  *UK fee payers only (see Terms and Conditions for further details).

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• Integrated Foundation Year (IFY)

  The Integrated Foundation Year (IFY) offers a new and exciting route into studying for a degree in Artificial Intelligence and Data Science, attracting ambitious and driven students who are willing to learn and advance.

  If you have non-standard qualifications or do not quite meet the admissions requirements we can offer you a fantastic opportunity to study a four year programme which includes an Integrated Foundation Year. The Integrated Foundation Year will help you develop the theoretical/practical and academic skills you need, in order to successfully progress to the full award.

  Our four-year courses will enable you to successfully follow the degree pathway of your choice while gaining essential study skills. The foundation year of your chosen degree will be studied on a full-time basis and is aimed at supporting the transition to higher education. Years two, three and four are then studied as a standard degree programme.

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• Frequently Asked Questions (FAQs)

  How will I learn on this Artificial Intelligence and Data Science degree?

  While theories are important for AI solutions, we emphasise  practical learning on our BSc Artificial Intelligence and Data Science course. You will be taught through a variety of activities and problem-solving challenges, so that you can apply your theoretical knowledge creatively. Being able to analyse problems, implement data science methods, research solutions, and apply them in new ways are highly valued in the computing industry. Armed with these tools, you will be able to use them throughout your career to drive the industry forward.

  You will have access to a dedicated AI lab with state-of-the-art equipment and software for learning. You will receive a laptop (Terms and Conditions apply) to work on your coursework flexibly.

  How will I be assessed?

  The AI and Data Science degree uses a range of assessment methods including assignments, portfolios, project reports, and video recordings. This comprehensive testing enables students to demonstrate their strengths in knowledge-based skills.

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