Overview

Mastering the computational principles, mathematical foundations, and algorithmic architectures of intelligent systems is central to leading the technological transformation across industry, medicine, and autonomous systems. The BSc (Hons) Computer Science (Artificial Intelligence) at University of Leeds, accredited by BCS (The Chartered Institute for IT), delivers a specialized education combining core software engineering with cutting-edge artificial intelligence techniques. Delivered by the School of Computing, the curriculum integrates software development, database systems, and computer architecture with advanced studies in machine learning, deep neural networks, computer vision, natural language processing, and robotics. Students gain practical experience in specialized computing laboratories equipped with GPU-accelerated clusters, development workstations, and AI frameworks. The program emphasizes algorithmic efficiency, software design patterns, and ethical AI development, offering opportunities for industrial work placements or study abroad. This degree is ideally suited for analytical, mathematically adept problem-solvers seeking to engineer intelligent algorithms, automate complex decision-making processes, and push the boundaries of computational science.

What You'll Learn

• Fundamental programming paradigms, algorithms, data structures, object-oriented software design, and software architecture using languages like Python, Java, and C++

• Mathematical foundations of computing, including discrete mathematics, linear algebra, calculus, probability theory, and statistical inference

• Core artificial intelligence techniques, knowledge representation, heuristic search, automated reasoning, and logic systems

• Machine learning principles, supervised and unsupervised learning models, deep learning architectures, reinforcement learning, and neural network design

• Computer vision and image processing, feature extraction, object recognition, motion tracking, and spatial computing applications

• Natural language processing (NLP), text mining, sentiment analysis, speech recognition, and generative AI models

• Software engineering practices, unit testing, agile project management, version control systems, and collaborative software development

• Ethical AI frameworks, algorithmic bias mitigation, privacy protection, safety assurance, and regulatory compliance in automated systems

• Independent computer science and AI capstone research project involving software engineering, model development, or algorithmic evaluation

Learning Outcomes

Graduates will possess an in-depth understanding of core computer science principles, software architecture, and specialized artificial intelligence methodologies. They will demonstrate the capability to design, implement, and evaluate machine learning models, autonomous algorithms, and scalable software systems using modern computational tools and frameworks. Students build strong technical abilities in high-level programming, software debugging, dataset analysis, and GPU computing through practical laboratory sessions and team software development projects. Furthermore, learners master the ability to communicate complex technical concepts, system architectures, and algorithmic performance metrics clearly to technical teams and non-specialist stakeholders. Through specialized module pathways and a major final-year individual capstone project, scholars cultivate the technical precision and problem-solving agility required to excel as AI engineers, machine learning specialists, software developers, data scientists, robotics engineers, tech consultants, or postgraduate computer science researchers.