MSc ACS: Artificial Intelligence / Course details

Year of entry: 2021

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Course description

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.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as the medical, health and life sciences and the humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Course unit list

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
Masters Project COMP66090 90 Mandatory
Automated Reasoning and Verification COMP60332 15 Optional
Modelling Data on the Web COMP60411 15 Optional
Principles of Digital Biology COMP60532 15 Optional
Introduction to Health Informatics COMP60542 15 Optional
Data Engineering COMP60711 15 Optional
Systems Governance COMP60721 15 Optional
Foundations of Machine Learning COMP61011 15 Optional
Representation Learning COMP61021 15 Optional
Text Mining COMP61332 15 Optional
Computer Vision COMP61342 15 Optional
Cryptography COMP61411 15 Optional
Cyber Security COMP61421 15 Optional
Software Engineering Concepts in Practice COMP61511 15 Optional
Querying Data on the Web COMP62421 15 Optional
Agile and Test-Driven Development COMP62521 15 Optional
Component-based Software Development COMP62532 15 Optional
Pattern-Based Software Development COMP62542 15 Optional
Software Security COMP63342 15 Optional
Displaying 10 of 19 course units

Additional fee information


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