- Start date: September
- Study mode and duration: 12 months, full-time
MSc conversion: No need for computer science as first degree
Places: capped at 60
Study with us
Studying a Masters in Artificial Intelligence & Applications at the University of Strathclyde, you'll be learning at an award-winning academic institution - the only to have won Times Higher Education University of the Year award twice.
Our AI Masters is designed specifically for graduates without a computing science background. It's a course in modern artificial intelligence, with a focus on intelligent agents and machine learning.
Artificial intelligence and machine learning skills are in wide demand. You'll gain skills to get ahead of the AI-driven transformation in our economy and society.
Why this course
Our MSc Artificial Intelligence & Applications is a conversion degree designed specifically for graduates without a computing science background.
It's based on the Office for Artificial Intelligence’s 2018 recommendations for AI Masters courses. You'll learn not just core AI-techniques, but how to place them within a business context so as to show their value.
A skills shortage, particularly around machine learning, means graduates are in high demand. This degree is designed to give you the skills to get ahead of the AI-driven transformation in our economy and society. You'll gain transferable skills to prepare you for a professional career in AI and its applications. These are expected to cover all aspects of society both within the tech sector, as well as outside, including:
Hear from Dr John Levine about our MSc Artificial Intelligence degree:
We've created this MSc to give you the skills you'll need to work with big data, deep learning and techniques for creating powerful autonomous systems.
Dr John Levine, senior lecturer
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Why choose us?
The focus of our Artificial Intelligence & Applications Masters programme is to equip you for the job market. At the end of the course you'll be able to:
- understand how AI algorithms, technologies and methodologies are designed, developed, optimised and applied at scale to meet business objectives
- select the appropriate statistical methods for sampling, distribution, assessment, bias and error
- understand AI problem structuring methods, and evaluate which methods are appropriate for a particular problem
- apply rigorous AI-methodologies through experimental design, exploratory modelling, and hypothesis testing to reach robust conclusions
- explain how such conclusions are reached to internal and external stakeholders
- understand how to extract data from systems, and ensure standards of data quality and consistency for processing by AI-systems
- integrate separate data sources in order to produce AI-solutions to meet user needs
- understand and make use of different types of data models
- understand how to build scalable machine learning technologies, and optimise them, to improve performance
- understand a range of software systems to build reliable, reusable, scalable AI solutions to time, quality and budget
- demonstrate why AI solutions meet user requirements to stakeholders and show the value gain associated to a given solution
- understand the range of applications of AI and how different application areas require different AI-technologies
Network with a range of employers
As a student within the Department of Computer & Information Sciences, you'll have opportunities to develop your profile as a computing professional and to network with a range of employers including:
- JP Morgan
- Morgan Stanley
- Goldman Sachs
- members of our Industrial Advisory Board are important contributors to our curriculum development and contribute via guest lectures
- depending on your specific interests, visits to Strathclyde's City Observatory or the Fab Lab will illustrate practical applications of computing
- employers and students interact at our IT Careers Fair arranged during the academic year
- our MSc dissertation projects are industry-focused and often industry-sponsored, with real-world topics; students are also encouraged to present or publish MSc findings at conferences
- our award-winning Careers Service will support your career planning through development sessions in topics such as interview skills, CV development and presentation skills
Legal, Ethical & Professional Issues (10 Credits)
This class ensures students are aware of the legal, social, ethical and professional issues commensurate with the practice of AI as well as, more broadly, information and data science.
Quantitative Methods for AI (10 Credits)
Quantitative methods such as linear algebra, probability, statistics, and calculus are needed to understand AI and to keep pace with its development. This course gives students the background in these topics they need.
Big Data Technologies (20 Credits)
This course gives students an understanding of the challenges posed by big data, an understanding of the key algorithms and techniques which are embodied in data analytics, and exposure to a number of different big data technologies and techniques.
AI for Autonomous Systems (20 credits)
This course covers gives a basic introduction to AI including topics such as intelligent search.
Deep Learning & Neural Nets (20 Credits)
The most impactful area of AI has been machine learning using neural networks. When combined with reinforcement learning, these neural networks can also become autonomous agents that can, for example, learn to play games to an extraordinarily high standard. This class will cover these two areas of AI.
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.
Machine Learning for Data Analytics (20 credits)
This class equips students 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.
Dissertation (60 Credits)
Students will undertake an individual 60 credit project under supervision, which should contain an element of original research. The 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). Assessment will include production of developed code, supporting written documentation, and practical demonstration.
Minimum second-class Honours degree or overseas equivalent.
|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 details of our English language teaching.
As a university, we now accept many more English language tests in addition to 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.
The University of Strathclyde is a great place to be as it combines a top-notch educational system mixed with amazing uni-life. It is everything and more I can ever think of for a university.
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.
AI graduates are highly employable. They can look forward to well-paid professional careers designing and building the digital technologies that underpin the global economy and, indeed, every aspect of human activity from recreation through healthcare to business and the natural environment.
Graduates are in high demand now and into the foreseeable future with skill shortages widely reported in the media and professional press (e.g. USAToday, 2017; Forbes, 2017). An average growth rate of 17% is predicted for 2014-2024, one of the highest average growth rates of all jobs (US Bureau of Labor Statistics, 2017).
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 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. Your programmes will be the key driver for the success of business
- Business/policy analyst: as a business/policy analyst you will identify improvements which can be made to organisational systems using AI, write specifications for their modification and enhancement, and be involved in the design of new IT solutions to improve business efficiency
Glasgow is Scotland's biggest & most cosmopolitan city
Our campus is based right in the very heart of Glasgow. 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.Life in Glasgow
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.
Start date: Sep 2022
Artificial Intelligence and Applications
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