A UK 2:1 honours degree, or its international equivalent, in informatics, artificial intelligence, cognitive science, computer science, electrical engineering, linguistics, mathematics, philosophy, physics or psychology.
Entry to this programme is competitive. A typical offer will normally require a UK first class honours degree.
Competent programming skills are essential. During your degree you must have completed a programming course in at least one of the following: C/C++, Java, Python, R, Matlab, Haskell, ML.
During your degree you must have completed the equivalent to 60 credits of mathematics that have typically covered the following subjects/topics: calculus (differentiation and integration), linear algebra (vectors and multi-dimensional matrices), discrete mathematics and mathematical reasoning (e.g. induction and reasoning, graph theoretic models, proofs), and probability (concepts in discrete and continuous probabilities, Markov chains etc.) Prior knowledge of probability concepts is especially important for this degree.
For 2020 entry we accept the following English language qualifications at the grades specified*:
IELTS: total 6.5 (at least 6.0 in each module)
TOEFL-iBT (including Special Home Edition): total 92 (at least 20 in each module). We do not accept TOEFL MyBest Score to meet our English language requirements
PTE Academic: total 61 (at least 56 in each of the "Communicative Skills" sections)
CAE and CPE: total 176 (at least 169 in each module)
Trinity ISE: ISE II with distinctions in all four components
For 2021 entry we will accept the following English language qualifications at the grades specified*:
IELTS: total 6.5 (at least 6.0 in each module)
TOEFL-iBT (including Special Home Edition): total 92 (at least 20 in each module). We do not accept TOEFL MyBest Score to meet our English language requirements
CAE and CPE: total 176 (at least 169 in each module)
Trinity ISE: ISE II with distinctions in all four components
*(Revised 21 February 2020 to remove PTE Academic from 2021 entry requirements. Revised 21 April 2020 to include TOEFL-iBT Special Home Edition in 2020 and 2021 entry requirements.)
Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, PTE Academic or Trinity ISE, in which case it must be no more than two years old.
This MSc is taught at the UK's longest established centre for artificial intelligence, which remains one of the best in the world.
Many of your courses will be taught by internationally known researchers spanning a wide range of areas in artificial intelligence and also drawing on research in related fields such as neuroscience, cognitive science, linguistics, and mathematics. We aim to give you the fundamental knowledge and practical skills needed to design, build, and apply AI systems in your chosen area of specialisation.
Compulsory courses:
Informatics Research Review
Informatics Project Proposal
Dissertation
In addition, about half your taught course credits must be chosen from areas of artificial intelligence. Course offerings follow the main research areas of our staff, with multiple course options available in natural language processing, machine learning, robotics, and related areas.
Example courses offered recently in artificial intelligence include:
Accelerated Natural Language Processing
For your remaining courses, you may choose further options from artificial intelligence or from a wide range of courses offered in other areas of Informatics, including computer systems, theoretical computer science, software engineering, and social and biological computation. Guidance is provided to help you choose a set of courses that work well together, giving you specialised expertise in your chosen area.
Advanced Vision
Automatic Speech Recognition
Decision Making in Robots and Autonomous Agents
Machine Learning & Pattern Recognition
Natural Language Understanding, Generation, and Machine Translation
Probabilistic Modelling and Reasoning
Reinforcement Learning
Robotics: Science and Systems
Our students are well prepared for both employment and academic research. The emphasis is on practical techniques for the design and construction of intelligent systems, preparing graduates to work in a variety of specialisms, from fraud detection software to recommendation systems and assistive robots.
