MSc Advanced Computer Science / Course details

Year of entry: 2024

Course description

With our Advanced Computer Science MSc, you will have the flexibility to tailor your learning and pursue the topics that interest you most. You will have the opportunity to choose four from eight academic themes, each of which combines two related course units. 

Certain combinations are integrated into specialised pathways , including artificial intelligence, computer security, data and knowledge management, and digital biology. 

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. With the Advanced Computer Science MSc, you will learn from world-leading academic staff to amplify your skills ahead of a successful career in either industry or academia.

Aims

  • You will progress down your own chosen pathway, taking advantage of the flexibility of units on offer.
  • You will boost your employability across nearly all areas of business and society, with the technical skills you acquire being in great demand.

Special features

Flexibility

You will choose four from eight themes, each of which combines two related course units.

Strong links with employers

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry.

Excellent facilities

You will have access to a fantastic range of facilities and equipment.

Teaching and learning

You can choose from a broad range of units, including core computer science topics and Digital Biology and Health Informatics.

Coursework and assessment

You will learn through a mix of lectures and seminars, and supported by practical exercises. These skills are augmented through an MSc project, enabling you to put into practice the techniques you have been taught throughout the course.

Course unit details

This course aims to impart advanced knowledge across a broad range of Computer Science, offering training in advanced skills. It is suitable for those who wish to enhance their computing skills in order to improve their contribution to IT-related industry or to pursue R&D in academia or industry. 

A student following the Advanced Computer Science course chooses four from eight themes, each of which combines two related course units that build on top of each other. Certain combinations are integrated into specialised pathways . A student who opts to follow the pathways will have the pathway specialism included in their degree certificate. 

For September 2024 entry, we are making several changes to our course unit offering. These changes are not yet reflected in the course unit list below, but are summarised here as follows:

Masters Project COMP66060 (60 credits)

This course unit remains mandatory but will be worth 60 credits instead of 90 credits. In this course unit you will learn about the dissertation project process, how to plan the project and how to write the dissertation, including ethical and professional considerations. We will provide you with the skills to undertake, manage and deliver a technical project in the broad field of computer science, over the course of approximately 3 months (June-August). 

The following two optional course units are being introduced under a new theme, which will be available to select in Semester 2: Decision Making Under Uncertainty .

Reasoning and Learning Under Uncertainty COMP64102 (15 credits)

Machine learning is increasingly being used for decision support in data driven applications. A key concept when making decisions based on predictive models is that of uncertainty, e.g., in applications of AI where safety or trustworthiness are required. Uncertainty quantification recognises that exact predictions are often out-of-reach due to theoretical or practical limitations. This course unit studies different probabilistic machine learning models that incorporate uncertain reasoning and the mathematical concepts and algorithms required to learn such models from data.

Reinforcement Learning COMP64202 (15 credits)

Reinforcement learning (RL) looks to create machine learning models that are able to make decisions. An agent learns to achieve a goal in an uncertain, potentially complex environment. Successful real-world applications include but are not limited to robotics, control, operation research, games, economics, and human-computer interactions. This course will cover the breadth of modern model-free RL methods, discuss their limitations, and introduce various current research topics. In particular, we expect to cover the following: deep learning methodology and architectures, stabilisation of approximated value estimation, modern actor-critic methods, planning as inference, exploration with deep networks, offline reinforcement learning, deep multi-agent reinforcement learning, multi-task and meta-learning.

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
Cognitive Robotics and Computer Vision COMP61342 15 Optional
Cryptography COMP61411 15 Optional
Cyber Security COMP61421 15 Optional
Querying Data on the Web COMP62421 15 Optional
Software Security COMP63342 15 Optional
Displaying 10 of 15 course units

Additional fee information

Scholarships and bursaries

Across our institution, we offer a number of postgraduate taught scholarships and awards to outstanding UK and international students each year.

The University of Manchester is committed to widening participation in master's study, and allocates £300,000 in funding each year. Our Manchester Masters Bursaries are aimed at widening access to master's courses by removing barriers to postgraduate education for students from underrepresented groups.

For more information, see the Computer Science Fees and funding page or visit the University of Manchester funding for masters courses website for more information.

What our students say

Find out what it's like to study at Manchester by visiting the Department of Computer Science blog .

Facilities

Our computer science facilities are second-to-none, with a vast range of leading equipment - including newly-refurbished computing labs furnished with modern desktop computers, and collaborative working labs boasting specialist computing and audio-visual equipment to support group working. In total, we have more than 300 computers across the Department of Computer Science.

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk