BSc (Hons) Computer Science with Artificial Intelligence

What facilities can I use?

BNU has invested in our facilities to ensure that you can learn on industry standard systems and software, meaning that you can make an easy transition from education into employment. Quite simply we are committed to making sure we provide you with the best learning experience possible.

We make sure we keep the University’s computing facilities well maintained and equipped. We have a range of large labs; some being enhanced with cyber and A.I. specific facilities. Furthermore, many of these rooms are filled with dual-screen, dual boot (Windows and Linux) systems. Latest industry standard software is also included on devices to allow you to develop your skills to what is needed in the workplace.

Labs have been custom built to provide the best spaces to nurture the specific skills needed for game and internet development. These allow you to build your skills within key areas of future employment.

Hands-on experience is what we are all about. We have numerous devices that will provide the basis for various supervised projects you will carry out across the programme. These include but are not limited to Virtual Reality headsets, 3D printers, Raspberry Pi microcomputers, EEG headsets.

Furthermore, we provide online facilities to enhance your independent learning, via our Virtual Learning Environment. This will provide you with access to additional material and collaborative learning tools 24/7. And our virtual server technology will allow you to use our operating systems remotely.

What will I study? 

As you start, you'll get to dive into both core computer science and specialised AI topics. The course starts with the basics like programming (in Python, Java, and C++), algorithms, software engineering, and database management, giving you a solid foundation in computing. You’ll also learn how computers work at a deeper level, studying operating systems and computer architecture.

As you progress, you’ll focus more on AI, starting with an introduction to how AI systems think and solve problems. You’ll study machine learning techniques, like neural networks and decision trees, and teaching computers how to learn from data. Later, you’ll explore deep learning, robotics, and natural language processing (such as voice assistants). Big data and data science also play a key role, teaching you how to handle large datasets and analyse data efficiently.

The degree also covers the math behind AI (probability, statistics, and calculus), and takes a look at the ethical side of AI, like privacy issues and how AI impacts society. In your final year, you’ll work on a major project, where you solve a real-world problem using AI. You may also get the opportunity for a work placement, to gain hands-on industry experience.

Optional modules let you dive into areas like cybersecurity, the Internet of Things (IoT), or user-friendly AI interfaces, depending on your interests. 

You will also get opportunities to expand your knowledge both inside and outside of the lecture theatre. Students have previously visited sites of historical importance, including Bletchley Park, to learn more about the history of computing and how it impacted the world.

How will I be taught and assessed?

You’ll be taught through a mix of lectures, practical lab sessions, workshops, and tutorials. Lectures provide the theoretical foundation, while lab sessions focus on hands-on coding and AI development. Workshops and seminars will allow for interactive learning and collaboration with your peers, while small-group tutorials offer personalised support. A significant portion of your learning will also come from independent study and project work, where you can explore topics in-depth.

Assessment is a combination of coursework, practical projects, exams, and presentations. Coursework includes programming assignments and research projects, while practical projects assess your ability to develop AI systems and software. Some modules will have written exams to test your theoretical knowledge, and in your final year, you’ll complete a major project on a real-world AI problem. Presentations and group work are also part of the assessment, ensuring you develop both individual and teamwork skills. This approach balances both practical and theoretical learning, preparing you for a career in AI and computer science.