ACS: Artificial Intelligence at University of Manchester - UCAS

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Course summary

Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent - so that they are able to learn from experience, to derive implicit knowledge from the one given explicitly, to understand natural languages such as English, Arabic, or Urdu, to determine the content of images, to work collaboratively together, etc. The techniques used in AI are as diverse as the problems tackled: they range from classical logic to statistical approaches to simulate brains. This pathway reflects the diversity of AI in that it freely combines a number of themes related to AI techniques, namely Making Sense of Complex Data, Learning from Data, Reasoning and Optimisation, and Advanced Web Technologies.


Entry requirements

We operate a selective staged admissions process. We give preference to students with the strongest grades from high-ranking institutions. Successful applicants typically hold a First-class honours degree (70% average) from a UK university, or the overseas equivalent, in a Computer Science degree with a minimum of 50% Computer Science content. We require that all applicants have a strong background in Computer Science reflected, for example, in solid programming and software development skills We accept a range of qualifications, and welcome applications from overseas applicants. A typical successful offer-holder will evidence: China: a minimum of 87% in a 4-year bachelor's degree from a well ranked institution. India: a minimum of 65% (First Class with Distinction) in a BSc Eng, BEng or BTech degree, depending on the institution. For further information on international entry requirements, please contact [email protected]


Fees and funding

Tuition fees

No fee information has been provided for this course

Additional fee information

Fees for entry in 2024 have not yet been set.
ACS: Artificial Intelligence at University of Manchester - UCAS