Overview

Designing intelligent computational systems, developing algorithmic models, and interrogating the foundational mechanics of machine learning are essential for driving innovation across modern science and global industry. The Artificial Intelligence BSc at King's College London provides a rigorous, software-focused technical education delivered within the Department of Informatics in the Faculty of Natural, Mathematical & Engineering Sciences. The curriculum spans six core dimensions of AI: foundational discrete mathematics and programming, data science and machine learning, knowledge representation and reasoning, optimization and planning, AI engineering, and the legal, social, and philosophical ethics of intelligent software. Taught by internationally recognized academics at the forefront of safe and trusted AI, autonomous systems, and natural language processing, students learn to design algorithms, train neural network models, and engineer cloud-based intelligent systems. The program combines theoretical rigor with practical software implementation, offering options to undertake an industrial placement year or study abroad. This course is ideally suited for mathematically adept, analytically driven individuals who wish to master computational principles, build autonomous algorithms, and pursue high-impact technical careers across AI engineering, robotics, software design, data science, and technology strategy.

What You'll Learn

• Fundamental concepts in programming practice, software engineering principles, algorithm design, and computational complexity

• Core mathematical foundations for artificial intelligence, including discrete mathematics, linear algebra, calculus, probability, and statistics

• Data science paradigms, supervised and unsupervised machine learning algorithms, deep learning, and natural language processing techniques

• Logic, formal verification, knowledge representation, ontology engineering, and automated reasoning frameworks

• Optimization methodologies, search strategies, automated planning algorithms, and autonomous agent systems

• AI engineering methodologies, web and internet systems, cloud computing infrastructure, and AI security and privacy protocols

• Fundamentals of autonomous robotics, sensor integration, computer vision, and physical control systems

• Philosophical frameworks, algorithmic bias mitigation, legal regulations, and safety considerations governing AI deployment

• Independent final-year individual capstone project designing, implementing, and evaluating an original artificial intelligence software system

Learning Outcomes

Graduates will possess an in-depth understanding of the mathematical principles, logical frameworks, and algorithmic architectures underpinning modern artificial intelligence systems. They will demonstrate the capability to analyze complex computational problems, design custom machine learning pipelines, evaluate algorithmic performance metrics, and build scalable, secure software solutions. Students acquire strong practical competencies in multi-paradigm programming, data engineering, statistical modeling, and software prototype development through lab workshops, code reviews, and individual software build projects. Furthermore, scholars master the ability to evaluate the legal, ethical, and societal impacts of intelligent technologies, communicating complex technical architectures and data-driven insights clearly to both expert computer scientists and non-specialist stakeholders. Through research-led teaching and exposure to King's Institute for Artificial Intelligence networks, graduates cultivate the technical precision, creative problem-solving agility, and ethical foresight required to excel as AI engineers, machine learning scientists, data architects, software developers, technology consultants, or postgraduate research scholars.