Program Overview

MSc Artificial Intelligence & Applications

The 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 National AI Strategy 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.

Key Facts

• Start date: September
• Study mode and duration: 12 months, full-time
• MSc conversion: No need for computer science as first degree

Course Overview

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 & Applications 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.

Course Content

The curriculum comprises 180 credits, with one credit being equal to ten hours of student learning. The curriculum includes 60 credits in Semester 1, 60 credits in Semester 2, and a 60-credit project that typically runs from May to August.

• Semester 1
• Semester 2
• Semester 3

Modules

• Legal, Ethical & Professional Issues (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.
• Quantitative Methods for AI (10 Credits): The aim of this module is to provide you with the foundations of mathematics that are required to understand modern Artificial Intelligence techniques.
• Big Data Technologies (20 Credits): This module aims to give you 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 module focuses on implementing AI algorithms and building autonomous systems.
• Deep Learning & Neural Nets (20 Credits): The most impactful area of AI has been machine learning using neural networks.
• AI for Finance (20 credits): This module provides an overview of the application of AI techniques to a range of financial applications such as forecasting, portfolio optimisation and algorithmic trading.
• Machine Learning for Data Analytics (20 credits): This module equips 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.
• Dissertation (60 Credits): You'll undertake an individual project under supervision, which should contain an element of original research.

Learning & Teaching

Each module is delivered through a combination of lectures, practical computer laboratory work, and tutorials. Module content is also made available online in our virtual learning environment, including recorded lectures and interactive exercises.

Assessment

Each module is assessed by combination of coursework and exam. The course includes both individual and group coursework assignments.

Entry Requirements

This programme is designed for graduates without a computing science background. If you have a computing science background, we recommend you apply for one of the following Advanced Computer Science pathways as you will not be made an offer for this programme.

• Academic requirements: Minimum second-class (2:2) 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).

Fees & Funding

All fees quoted are for full-time courses and per academic year unless stated otherwise.

• Scotland: £11,900
• England, Wales & Northern Ireland: £11,900
• Republic of Ireland: If you are an Irish citizen and have been ordinary resident in the Republic of Ireland for the three years prior to the relevant date, and will be coming to Scotland for Educational purposes only, you will meet the criteria of England, Wales & Northern Ireland fee status.
• International: £28,700

Careers

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.

• 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.
• AI Engineer (for Autonomous Systems): In this role, you will focus on designing AI systems that enable machines or robots to operate autonomously.
• 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

Research Areas

The teaching staff have a range of research interests, including:

• Joseph El Gemayel (Course Director): My interest is in building Autonomous Adaptive and Self-Learning Multi-Agent Systems.
• Professor Crawford Revie: Much of my research takes place at the intersection of informatics and the life sciences; I have worked extensively with data-driven models of disease and host-parasite dynamics in both human and animal populations.
• Dr Emma Nicol: My main research interests are Information Behaviour and Human Computer Interaction (HCI).
• Dr William Bell: My work has involved constructing new analysis approaches to standard model measurements and searches.
• Dr Mohamed Elawady: My research expertise involves image analysis, robotics vision, information retrieval and medical imaging.
• Dr Yashar Moshfeghi: I'm a Senior Lecturer in Artificial Intelligence and Data Science here at the University of Strathclyde, where I founded and lead the NeuraSearch Laboratory.
• Dr Leif Azzopardi: I'm an Associate Professor in Artificial Intelligence and Data Science, where I lead the Interaction Lab (i-lab).
• Dr Keith Smith: My research involves developing tools and theory for the analysis of brain and biological networks with applications to various conditions including dementia, major depressive disorder, and preterm birth.
• Professor Feng Dong: Feng Dong is a Professor of Computer Science, Head of the Human Centric AI research group at the University of Strathclyde, UK.