MSc Advanced Computer Science
ApplyKey facts
- Start date: September
- Study mode and duration: 12 months full-time
Research project: opportunity to undertake your research project with one of our external partners
Study with us
Studying an MSc in Advanced Computer Science at the University of Strathclyde, you'll be learning at an award-winning academic institution - the only University to have won the Times Higher Education University of the Year award twice (2012/2019).
- an advanced Masters designed for graduates with a degree in computer science or a related discipline, with significant programming experience
- choose from a broad range of optional modules to match your interests and career aspirations
- guest lectures from leading employers and our expert alumni
- skilled computer science professionals are in high demand
- Prefer to start your course in January? We also offer our MSc Advanced Computer Science (January intake).
You may also be interested in:
Why this course?
Computer science supports the build, development and use of computer systems. Systems development is of crucial importance in many areas of modern life. As new technologies continue to emerge, there's a growing worldwide need for skilled, expert computer science professionals.
Our MSc in Advanced Computer Science has a small number of compulsory modules, supplemented by a wide variety of optional modules. You can choose from this range of optional modules to tailor your own programme of advanced study to meet your academic interests and career aspirations - whether your interests relate to software engineering or data science.
Engage with industry
Throughout the course, we offer opportunities to engage with industry through IT careers fairs, guest lectures from local industry, industrially sponsored projects, specialist sessions from our University Careers Service and student demo days to industry.
Why choose Strathclyde?
In the video below, Marut tells us why he chose to study with us:
Chat to a student ambassador
If you want to know more about what it’s like to be a Science student at the University of Strathclyde, a selection of our current students are here to help!
Our Unibuddy ambassadors can answer all the questions you might have about courses and studying at Strathclyde, along with offering insight into their experiences of life in Glasgow and Scotland.
Chat now!What you’ll study
On our Advanced Computer Science Masters, you’ll study two 11-week semesters, each with three or four modules.
Each module typically has four hours of lectures, laboratory practicals and/or tutorials. Additional study time is required to enhance and apply your understanding of the topics covered, through further reading, self-directed study and assignments.
In the summer, between June and August, you’ll undertake an in-depth three-month research project.
A range of software systems are used to build reliable, scalable and quality solutions, and you will apply rigorous methodologies through experimental design and exploratory modelling. For example:
- the deep learning module allows you to use popular APIs such as Keras and Tensorflow
- topics such as reinforcement learning for real-world “game” play e.g AlphaStar
- you'll become familiar with a number of different cloud NoSQL systems and the Map-Reduce programming paradigm
- evolutionary computation techniques such as genetic algorithms, genetic programming and neural networks will be introduced to a range of financial applications
Research project
Our project supervision programme ensures a named academic is attached to every MSc student during their project study between May and August each year. View all our academic experts in the Department of Computer & Information Sciences. Regular meetings are scheduled during the period of the project work, and where an external organisation is involved, meetings between supervisor, student and external body are standard. We have extensive experience of supporting students in placement and thus are well equipped and experienced to manage both university and placement provider expectations.
Facilities
The course will involve some extensive laboratory-based instruction and student work. The Department of Computer and Information Sciences utilise their own specialist laboratories to provide practical student tuition on large-scale advanced applications.
The University library also has a sufficient body of resources to support this course.
Compulsory modules
Legal, Ethical and Professional Issues for the Information Society (10 credits)
This module aims to ensure that you're aware of the legal, social, ethical and professional issues commensurate with the practice of Information Systems Engineering.
Elective modules
Select 100 credits from the elective modules below, across semesters 1 and 2. Please note, elective modules are subject to change.
Advanced Topics in Software Engineering (20 credits)
This module aims to:
- make you aware of key aspects of current software engineering research
- familiarise you with the state-of-the-art in terms of what problems can be solved and what are the current exciting challenges
- equip you with the necessary skills to allow you to contribute to the software engineering research community
- equip you with the skills and background to appreciate the contributions to software engineering research across the full range of material presented at the key international conferences in the field
Designing Usable Systems (20 credits)
In this module, you'll develop research-level understanding of the design and evaluation of interactive systems and interfaces for newly emerging technologies and computing domains, such as:
- ubiquitous and mobile computing
- universal access
- domain-specific applications (e.g. older adults, education, health, children)
Information Retrieval (10 credits)
You'll learn to:
- critically examine a number of influential information-seeking models
- provide an understanding of research methodologies for studying human information behaviour
- examine important concepts, such as relevance, in the context of information seeking and retrieval
- examine how findings from information seeking theory and practise can inform the design of information access systems
- outline the theory and technology used to construct modern Information Retrieval and Access systems
- critically evaluate the assumptions behind the evaluation of Information Retrieval systems
Deep Learning Theory and Practice (20 credits)
By the end of the module you should be able to:
- understand the challenges in the training of deep neural network and how to overcome the challenges with few shot learning techniques
- understand how to process sequential data with deep neural network and the applications in natural language processing
- develop understanding of the potentials and generalisation of deep neural networks through theoretical analysis
- understand deep generative models and their main approaches
- understand how to build Deep Neural Networks in Python using packages such as Keras/PyTorch and implement such networks
Big Data Technologies
20 credits
In this module you will learn to:
- understand the fundamentals of Python to enable the use of various big data technologies
- understand how classical statistical techniques are applied in modern data analysis
- understand the potential application of data analysis tools for various problems and appreciate their limitations
- be familiar with a number of different cloud NoSQL systems and their design and implementation, showing how they can achieve efficiency and scalability while also addressing design trade-offs and their impacts
- be familiar with the Map-Reduce programming paradigm
Project Management (20 credits)
This module will help you:
- appreciate the practicalities of project evaluation and management
- understand and use techniques for the evaluation, planning and management of projects
- examine the issues and problems in being a project manager
- gain an appreciation of the project environment
Compulsory modules
Research Methods (10 credits)
This module aims to provide you with an understanding of both quantitative and qualitative research processes and associated techniques, including the effective presentation of findings in accordance with the best principles of scholarship.
Elective modules
Mobile Software & Applications (20 credits)
By the end of the module you should be able to:
- appreciate and explain the problems associated with mobile software environments
- identify and explain the models and techniques typically employed in the design and development of a range of software for mobile environments, and appreciate the limitations of these
- appreciate the role and impact of context-awareness and persuasion in modern mobile applications
- demonstrate the ability to implement selections from a range of the software typically used in mobile environments
Distributed Information Systems (20 credits)
This module will give you an extended understanding of the deep, technical issues underlying information systems, in the particular context of distributing content over the world-wide web.
Machine Learning for Data Analytics (20 credits)
The aim of this module is to equip you with a sound understanding of the principles of machine learning and a range of popular approaches, along with the knowledge of how and when to apply the techniques. The module balances a solid theoretical knowledge of the techniques with practical application via Python (and associated libraries) and students are expected to be familiar with the language. Aspects of the course will be highly mathematical and technical requiring strong math and programming ability (Python and Tensorflow).
Business Analysis (10 credits)
This module aims to provide tools and techniques for the effective analysis and design of business information systems and enable you to develop an understanding of their respective advantages, disadvantages and applicability.
Game Theory and Multi-Agent Systems (10 credits)
This module consists of about two-thirds game theory and about one-third reinforcement learning, although the two topics blend into each other. We'll also touch on some other points of contact between game theory and AI.
Evolutionary Computing for Finance (20 credits)
On completion of this module you'll:
- gain an understanding of a range of evolutionary computational and machine learning techniques
- gain an understanding of the relative advantages and disadvantages of each technique for different financial applications
- be able to evaluate the results of a financial problem investigated using evolutionary computation and machine learning techniques
60 credits
Over the summer semester, from June until August, you'll undertake a significant piece of work that will be your MSc project. This is typically a very practical activity, and can include:
- analysing a problem and designing, implementing and evaluating a solution
- conducting an in-depth experimental analysis of technique or technology
- performing an analysis of a large data set, and building and evaluating models of the data
We'll also have a range of projects available that are sponsored by our staff based on their latest research, and many that come directly from the employers we work with, representing real-world problems they are trying to solve.
Learning & teaching
Our teaching and learning methods include lectures, tutorials, laboratory practicals and combinations of individual and group work. These will not only develop your expertise in computer science, but also in communication, team-working and analytical skills which are all essential skills for your future career.
Class material will be placed on Myplace for you to gain access to in your own time. A personal computer is required to access teaching materials and attend online lectures/meetings. The computer lab is also available for all students to use.
You’ll have regular contact with our expert staff, many of whom have been nominated for, and won, teaching awards based on nominations by our students.
Assessment
Assessment is through a combination of individual work, group work, exams and practical work in laboratories. Around half the classes are assessed entirely by coursework, the others are a combination of coursework and examination.
During the course I have developed an understanding and appreciation of academic research, machine learning and optimization algorithms, static and dynamic analysis, frameworks and programming styles, and semantic web.
Entry requirements
| Academic requirements / experience |
|
|---|---|
| English language requirements | You must have an English language minimum score of IELTS 6.0 (with no component below 5.5). We offer comprehensive English language courses for students whose IELTS scores are below 6.0. Please see ELTD for full details. As a university, we now accept many more English language tests other than IELTS for overseas applicants, for example, TOEFL and PTE Cambridge. View the full list of accepted English language tests here. |
Pre-Masters preparation course
The Pre-Masters Programme is a preparation course held at the University of Strathclyde International Study Centre, for international students (non-UK/Ireland) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde.
Upon successful completion, you'll be able to progress to this degree course at the University of Strathclyde.
Please note: Previous Maths & English qualifications and your undergraduate degree must meet GTCS minimum entry requirements as well as the pre-Masters course and an interview will be conducted before an offer can be made.
Fees & funding
All fees quoted are for full-time courses and per academic year unless stated otherwise.
Fees may be subject to updates to maintain accuracy. Tuition fees will be notified in your offer letter.
All fees are in £ sterling, unless otherwise stated, and may be subject to revision.
Annual revision of fees
Students on programmes of study of more than one year (or studying standalone modules) should be aware that tuition fees are revised annually and may increase in subsequent years of study. Annual increases will generally reflect UK inflation rates and increases to programme delivery costs.
| Scotland | £10,800 |
|---|---|
| England, Wales & Northern Ireland | £10,800 |
| International | £27,500 |
| Available scholarships | Take a look at our scholarships search for funding opportunities. |
| Additional costs | If you are an international student, you may have associated visa and immigration costs. Please see student visa guidance for more information. |
Please note: the fees shown are annual and may be subject to an increase each year. Find out more about fees.
How can I fund my course?
Scottish postgraduate students
Scottish postgraduate students may be able to apply for support from the Student Awards Agency Scotland (SAAS). The support is in the form of a tuition fee loan and for eligible students, a living cost loan. Find out more about the support and how to apply.
Don’t forget to check our scholarship search for more help with fees and funding.
Students coming from England
Students ordinarily resident in England may be to apply for postgraduate support from Student Finance England. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Don’t forget to check our scholarship search for more help with fees and funding.
Students coming from Wales
Students ordinarily resident in Wales may be to apply for postgraduate support from Student Finance Wales. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Don’t forget to check our scholarship search for more help with fees and funding.
Students coming from Northern Ireland
Postgraduate students who are ordinarily resident in Northern Ireland may be able to apply for support from Student Finance Northern Ireland. The support is a tuition fee loan of up to £5,500. Find out more about the support and how to apply.
Don’t forget to check our scholarship search for more help with fees and funding.
International students
We've a large range of scholarships available to help you fund your studies. Check our scholarship search for more help with fees and funding.
International students
We've a thriving international community with students coming here to study from over 140 countries across the world. Find out all you need to know about studying in Glasgow at Strathclyde and hear from students about their experiences.
Visit our international students' section
Careers
There will be opportunities for you to meet industry employers and take part in recruitment events, in addition to taking advantage of a wealth of support offered by our careers service.
We have a dedicated careers fair for our computer science and information management students each year, with over 30 leading companies, including:
- Amazon
- JP Morgan
- Morgan Stanley
- British Telecom
- Bridgeall
- Kana
- Skyscanner
- ThinkAnalytics
As a graduate you could progress to be an analyst, architect or developer. There's a demand for advanced practitioners and researchers in the growing area of embedded systems development.
How much will I earn?*
| Role | Potential earnings |
|---|---|
| Systems Analyst | Junior analysts can expect to earn between £20,000 and £25,000, while more experienced analysts earn, on average, in excess of £40,000. |
| Applications Developer | Graduate salaries for applications developers start at around £20,000. Once established, you can expect to earn £34,000 to £40,000. As a senior applications developer, your salary will be in the region of £45,000 to £70,000. |
| Machine Learning Engineer | As a graduate starting out in your career, you can expect a salary of around £35,000. The average salary for a machine learning engineer in the UK is £52,000. This can rise to as much as £170,000 if you work for a large multinational company like Google or Facebook. |
| Data Scientist | Salaries for junior data scientists tend to start at around £25,000 to £30,000, rising to £40,000 depending on your experience. With a few years' experience you can expect to earn between £40,000 and £60,000. Lead and chief data scientists can earn upwards of £60,000, in some cases reaching more than £100,000. |
| Software Engineer | Typical graduate software engineer salaries start from £18,000 a year. The average annual salary for a software engineer is between £25,000 and £50,000. At senior or management level, software engineers can earn £45,000 to £70,000 or more per annum. Bonus schemes may be available. |
*Information is intended only as a guide. Salary information acquired from Prospects, June 2022.
Apply
There is currently no deadline for submitting applications. However, we encourage you to apply early as we consider applications on a first come, first served basis, and may introduce an application deadline due to high demand.
Please ensure you upload evidence to support your programming experience; degree transcript and/or detailed CV if your degree is over five years old.
To apply for January 2024 entry, please visit MSc Advanced Computer Science (January start)
Start date: Sep 2024
Advanced Computer Science
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