BSc Computer Science & Artificial Intelligence With Stem Foundation Year
About this course
Computer science and artificial intelligence is the combination of the foundational discipline of computation with the field that has become one of the most consequential areas of applied science in the contemporary world. Computer science examines how problems can be solved algorithmically, how data structures enable efficient computation, how software systems are built and how the theory of computation places fundamental limits on what machines can do. Artificial intelligence applies these foundations to build systems that can learn from data, reason about uncertain situations, recognise patterns in complex inputs and act intelligently in real-world environments. Together these disciplines give you both the theoretical grounding and the practical skills to work at the frontier of intelligent systems development. At Edge Hill University, this four-year full-time degree includes a STEM foundation year, which provides the mathematical and scientific preparation needed for students entering from a non-traditional background or who benefit from additional foundation in the subject areas. The foundation year covers the key scientific and computational skills needed to progress successfully into the main computer science and AI degree. You will then study the core of computer science alongside machine learning, neural networks, natural language processing, computer vision, intelligent agents and the mathematical foundations of artificial intelligence. Typical entry is around 120 UCAS tariff points. Graduates are in high demand across the technology sector, in roles including machine learning engineering, data science, software development, AI research, robotics and intelligent systems design. Virtually every major industry, from healthcare and finance to logistics and entertainment, is now investing in AI capabilities, and graduates who combine strong software engineering fundamentals with AI expertise are particularly well positioned. Many graduates also continue to postgraduate research in machine learning, computer vision, natural language processing or robotics.
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