(Full time) 2019 start
Advanced Computer Science (Cloud Computing) MSc
Overview
Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science.
You’ll gain a foundation in topics like systems programming and algorithms, as well as specialist modules in advanced distributed systems – especially cloud techniques, technologies and applications.
Building on your existing knowledge of computer science, you’ll also choose from optional modules in topics across computer science. You could look at emerging approaches to human interaction with computational systems, data mining and functional programming among others.
The programme will give you the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.
Specialist facilities
You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.
We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.
Course content
Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming. Throughout the year you’ll also take modules developing your understanding of cloud computing itself, from designing the high-level framework of a distributed system to big data and the “internet of things”.
From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, machine learning, semantic technologies and developing mobile apps.
Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.
Want to find out more about your modules?Take a look at the Advanced Computer Science (Cloud Computing) module descriptions for more detail on what you will study.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
Modules
Year 1
Compulsory modules
- MSc Project 60 credits
- Cloud Computing 15 credits
Optional modules (selection of typical options shown below)
- Web Services and Web Data 10 credits
- Distributed Systems 10 credits
- Mobile Application Development 10 credits
- Machine Learning 10 credits
- Information Visualization 10 credits
- Combinatorial Optimisation 10 credits
- Secure Computing 10 credits
- Graph Algorithms and Complexity Theory 10 credits
- Big Data Systems 15 credits
- Data Science 15 credits
- Bio-Inspired Computing 15 credits
- Knowledge Representation and Reasoning 15 credits
- Algorithms 15 credits
- Parallel and Concurrent Programming 15 credits
- Data Mining and Text Analytics 15 credits
- Semantic Technologies and Applications 15 credits
- Image Analysis 15 credits
- Scheduling 15 credits
- Scientific Computation 15 credits
- Graph Theory: Structure and Algorithms 15 credits
Learning and teaching
Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.
Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.
Assessment
You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
Applying, fees and funding
Entry requirements
A bachelor degree with a 2:1 (hons) in computing or a related subject with a substantial computing element. Relevant work experience will also be considered.
We expect you to have programming competence, some prior experience of systems development and knowledge of data structures and algorithms.
All applicants will need to have GCSE English Language at grade C or above, or an appropriate English language qualification.
We accept a range of international equivalent qualifications.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any component.. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Engineering (6 weeks) and Language for Science: Engineering (10 weeks).
If you need to study for longer than 10 weeks, read more about our postgraduate pre-sessional English course.
How to apply
Application deadlines
Applicants are encouraged to apply as early as possible for taught postgraduate programmes. The Faculty of Engineering will only consider applications made before the dates below, subject to places being available:
31 July – International Applicants
10 September - UK/EU applications
This link takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Admissions policy
Faculty of Engineering Postgraduate Admissions Policy 2019
Fees
- UK/EU: £10,500 (total)
- International: £22,000 (total)
Read more about paying fees and charges.
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.
For fees information for international taught postgraduate students, read Masters fees.
Brexit
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs
Scholarships and financial support
The School of Computing offer a range of scholarships for UK, EU and International students. Find out more about our Scholarships.
Career opportunities
Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.
This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.
Graduates have found success in a wide range of careers working as business analysts, software engineers, web designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.
Careers support
You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual STEM Careers Fairs provide further opportunities to explore your career options with some of the UKs leading employers.
The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.
Projects
The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.
Recent projects for MSc Advanced Computer Science (Cloud Computing) students have included:
- Intelligent services to support sensemaking
- Google cloud data analysis
- Hadoop for large image management
- Evaluating web service agreement in a cloud environment
A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.