MSc in Artificial Intelligence

The MSc in Artificial Intelligence is a taught postgraduate course aimed at graduates in disciplines with a large mathematics component, such as Mathematics, Physics and some types of Engineering. To apply, it is not necessary to have studied computer science previously.

The programme includes specialised intensive training in programming and AI, with a wide choice of elective modules, a group project and a large individual project. Students are encouraged to do both group and individual projects in collaboration with leading companies working on applications of AI.

The course will enable graduates to master the mathematical skills to understand and implement modern statistical machine learning methods, to master the logical foundations of AI, to master a variety of current AI and machine learning techniques and develop insight into problems involved in their application, develop the ability to evaluate the effectiveness of particular implementations, and develop the ability to deal with real-world data and scenarios and to apply and adjust techniques to realistic applications.

This course is also a suitable preparation for PhD studies.

If you have further questions regarding the degree which are not answered here or elsewhere on the website, please contact the admissions tutor for the MSc in Artificial Intelligence at doc-mscadmissions@imperial.ac.uk.

Artificial Intelligence in the Department of Computing

The Department of Computing at Imperial College London has active research groups in Artificial IntelligenceData Science, and Visual Computing. Many other groups and members of our research staff also work on theory, methods and applications of artificial intelligence and machine learning, and there are many collaborations with other departments at Imperial, as well as with industry.

We also house dedicated research centres, including the Dyson Robotics Lab, the Data Science Institute, the Centre for Integrative Systems Biology and Bioinformatics, the Hamlyn Centre for Medical Image Computing and Robotics, and more. Also, see the Imperial AI network for coordinated AI activity and collaboration throughout the college.

Graduates of the department with a focus on AI have gone on to work in the AI sections of such leading companies as DeepMind, Facebook, Google, and Twitter; many also progress to PhD research at Imperial and elsewhere. A graduate of the department recently had an AI company he co-founded valued at $1 billion, and two other graduates sold their AI startup to Twitter for $150 million.

Entry requirements

Applicants for this degree must possess the equivalent of a first-class UK degree in Mathematics, Physics, Engineering or other degrees with substantial mathematics content.

How to apply and application deadline

Applications for 2019 entry are now closed.

Applications for October 2020 entry are expected to open in October 2019. How to apply.

The deadline for applications for October 2020 entry is July 31st 2020. However, please be advised that we reserve the right to close applications before this date. For this reason, and because the number of places is limited, we recommend applying sooner rather than later.

Degree structure

The MSc in Artificial Intelligence consists of six compulsory modules and five chosen modules. For the chosen modules, students select at least four from the list of selective modules, at most one from the list of optional modules, summing to five. The group project mostly runs in the spring term; the individual project mostly runs over the summer.

Please note that the exact list of modules offered may be subject to change.

Compulsory modules

Introduction to Machine Learning.
Introduction to Symbolic Artificial Intelligence.
Python Programming.
Software Engineering Practice and Group Project.
Ethics, Privacy, AI in Society.
Individual Project.

Selective modules

Computer Vision.
Robotics.
Reinforcement Learning.
Machine Arguing.
Knowledge Representation.
Mathematics for Machine Learning.
Prolog.
Systems Verification.
Logic-Based Learning.
Machine Learning for Imaging.
Advanced Robotics.
Deep Learning.
Probabilistic Programming.
Computational Optimisation.
Natural Language Processing.
Probabilistic Inference.
Modal Logic for Strategic Reasoning in AI.

Optional modules

Separation Logic: Scalable Reasoning about Programs.
Scalable Systems and Data.
Computational Finance.
Complexity.
Advanced Computer Security.
Quantum Computing.
Databases.
Advanced Databases.
Network and Web Security.
Performance Engineering.
Principles of Distributed Ledgers.

Non-credit

As a non-credit component of the MSc in AI, students can also take:

Introduction to Prolog.