- Start date: September
- Study mode and duration: 12 months full-time
Number of students: maximum of 60
Study with us
- an advanced Masters degree for graduates with significant programming experience and a degree in Computer Science or a related discipline
- choose from a broad range of optional modules to match your interests and career aspirations
- guest lectures from leading employers and our expert alumni
Why this course
Artificial intelligence is found in all aspects of modern society, from the technologies that underpin the economy and how we work, to recreation, healthcare and even the natural environment. Its potential applications are growing daily.
Our MSc in Advanced Computer Science with Artificial Intelligence has been designed to meet the growing worldwide demand for skilled computer science professionals who have expertise in artificial intelligence.
Throughout our MSc you’ll develop an understanding of how artificial intelligence algorithms and technologies are designed, developed, optimised and applied to meet business objectives. You’ll learn to use a range of software systems that can be used to build reliable, scalable and quality artificial intelligence solutions, and how to apply rigorous AI methodologies through experimental design and exploratory modelling. You’ll also study the ethics of artificial intelligence applications and how different applications require different AI technologies.
Our programme will develop your expertise in many of the most widely used artificial intelligence techniques and applications. You'll also have the opportunity to choose from a wide range of optional modules to tailor your masters degree to meet your academic interests and career aspirations.
Graduates of the programme will have acquired the key skills to enable a successful career as an AI practitioner, advanced problem analysis and evaluation skills, and the ability to evaluate and communicate the results of artificial intelligence interventions to non-expert stakeholders.
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You’ll study two eleven-week semesters, each with 3-4 modules.
Each module typically has four hours of lectures, laboratory practicals and/or tutorials, with additional study time required to enhance and apply your understanding of the topics covered through further reading, self-directed study and assignments.
Between June and August you will undertake an in-depth three-month research project.
Legal, Ethical & Professional Issues for the Information Society
This class ensures you are aware of the legal, social, ethical and professional issues commensurate with the practice of artificial intelligence as well as, more broadly, information and data science.
Quantitative Methods for Artificial Intelligence
Underlying artificial intelligence there are a lot of quantitative methods such as linear algebra, probability, statistics, and calculus. This course will give you the necessary background in these topics.
Deep Learning Theory & Practices
This module provides an understanding of the key algorithms and techniques for deep learning, as well as an understanding of the limitations of the current technologies and their future trends.
Planning with Uncertainty
In order for a system to be regarded as autonomous, it has to make its own decisions about what actions to take in the world. In order for these to be regarded as intelligent decisions, the actions the system takes have to lead to desirable states of the world. This in turn requires two things: that the world and possible actions be represented somehow and that the system can deliberate about possible courses of action. This class will cover this crucial and fundamental area of artificial intelligence.
Deep Learning in Visual Computing Applications
This module will cover an in-depth application of neural networks including convolutional neural networks (CNN), recurrent neural networks (RNN) and deep neural networks. Using these methods, the module will also explore topics such as visualisation of features, model explainability, object detection, image segmentation and image generation.
Game Theory & Multi-agent Systems
This class will cover core game theory topics and AI-specific extension topics. Example topics include reinforcement learning for real-world “game” play e.g AlphaStar, and the behaviour of pricing algorithms interacting in a market.
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
You can choose 30 credits of elective classes from the following options to tailor your studies to your personal and career aspirations.
Mobile Software & Applications (20 credits)
This module aims to develop an understanding of the underpinning theories, paradigms, algorithms and architectures for building software applications to function in mobile computing environments.
AI for Finance (20 credits)
This class provides an overview of the application of AI techniques including those which mimic natural evolutionary processes (genetic algorithms and genetic programming in particular) to a range of financial applications such as forecasting, portfolio optimisation and algorithmic trading.
Distributed Information Systems (20 credits)
This module aims to help you develop an extended understanding of the deep technical issues underlying information systems in the particular context of distributing content over the world-wide web.
Fundamentals of Machine Learning for Data Analytics (10 credits)
The aim of this class 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 class balances a solid theoretical knowledge of the techniques with practical application via Python (and associated libraries). You are expected to be familiar with the language.
Information Retrieval (10 credits)
This class provides an overview of the field of information retrieval and explains how search systems and search engines work.
Business Analysis (10 credits)
This class aims to provide tools and techniques for the effective analysis and design of business information systems and enables you to develop an understanding of their respective advantages, disadvantages and applicability.
Evolutionary Computation For Finance 1 (10 credits)
This class provides an overview of the application of evolutionary computation techniques – those which mimic natural evolutionary processes (genetic algorithms, genetic programming and neural networks in particular) – to a range of financial applications such as forecasting and portfolio optimisation. This class cannot be combined with the AI for Finance elective.
Big Data Tools & Techniques (10 credits)
The aim of this module is to provide an understanding of the new challenges posed by the advent of big data, as they refer to its modelling, storage, and access; and an exposure to a number of different big data technologies and techniques, to show how they can achieve efficiency and scalability while also addressing design trade-offs and their impacts.
Over the summer semester, from June until August, you will undertake a significant project containing an element of original research, supervised by one of our expert academics.
Your project will be AI-application based (i.e. analysing, specifying, building and evaluating an AI-application or demonstrator, and forming recommendations and conclusions on the relative merits of the technologies involved and the methodologies used).
We will also have a range of projects available that are sponsored by our staff based on their latest research, and many that come direct 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 and artificial intelligence, but also in communication, team-working and analytical skills which are all essential skills for your future career.
You’ll have regular contact with our expert staff, many of whom as well as being leading international researchers have been nominated for, and won, teaching awards based on nominations by our students.
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.
|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 tuition for students whose IELTS scores are below 6.0.
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 EU/UK) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde. The Pre-Masters programme provides progression to a number of degree options.
Upon successful completion, you'll be able to progress to this degree course at the University of Strathclyde.
We've a thriving international community with students coming here to study from over 100 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
Fees & funding
All fees quoted are for full-time courses and per academic year unless stated otherwise.
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.
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.
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.
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.
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.
Glasgow is Scotland's biggest & most cosmopolitan city
Our campus is based in the very heart of Glasgow, Scotland's largest city. National Geographic named Glasgow as one of its 'Best of the World' destinations, while Rough Guide readers have voted Glasgow the world’s friendliest city! And Time Out named Glasgow in the top ten best cities in the world - we couldn't agree more!
We're in the city centre, next to the Merchant City, both of which are great locations for sightseeing, shopping and socialising alongside your studies.
Find out what some of our students think about studying in Glasgow!Find out all about life in Glasgow
Graduates will have developed the expertise to pursue a career directly in the applications of artificial intelligence, a field where skilled graduates are well-paid and in high demand. You can look forward to careers designing and building the digital technologies that underpin the global economy and, indeed, every aspect of human activity from recreation to healthcare to business.
Artificial Intelligence skills are also becoming increasingly important across multiple industries and graduates will be well equipped to pursue a career in a multi-disciplinary setting where a combination of their existing skills, artificial intelligence knowledge and analytical skills will be required.
Throughout the programme 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 award-winning careers service.
We have a dedicated careers fair for our computer science and information management students each year, with over 30 leading companies, including:
- JP Morgan
- Morgan Stanley
- British Telecom
Job market analysis shows that the most in-demand key skills include big data, machine learning and neural networks, all of which are central to this degree. Example roles could include:
- AI professional: businesses have a range of needs for which they need AI professionals. This can include to do things like deploy state of the art AI chatbots, developing image classifiers, creating computer vision applications or planning for autonomous vehicles. This degree provides you with the core skills to be able to deliver these needs.
- Data Scientist: businesses generate huge amounts of data every day and all want to clean that data, understand that data, extract information from that data and turn that information into information to drive the business forward. This degree gives you exactly the skills needed to perform these roles.
- Software developer: as a software developer you'll be playing a key role in the design, installation, testing and maintenance of the AI-technologies that are set to transform the world.
- Business/policy analyst: as a business/policy analyst you will identify improvements which can be made to organisational systems using artificial intelligence, write specifications for their modification and enhancement, and be involved in the design of new IT solutions to improve business efficiency.
Please note there is no deadline for submitting applications.
Start date: Sep 2022
Advanced Computer Science with Artificial Intelligence
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