Course summary
Machine learning and deep neural network systems are currently used by leading organisations worldwide and research centres in a wide range of applications and products. This course is for engineers and scientists looking to gain the necessary skills to be able to design these systems for use in industry. Our MSc Machine Learning & Deep Learning degree focuses on state-of-the-art technologies for machine learning and deep neural network systems. The emphasis is on architectures, algorithms and implementation with applications in a diverse range of areas. Delivered jointly by the Departments of Electronic & Electrical Engineering and Computer & Information Sciences, you'll be exposed to state-of-the-art engineering and software technologies that underpin machine learning and deep neural network systems. You'll learn about and gain experience from hands-on, industry relevant projects and examples. This includes programming languages and engineering tools used in an increasing number of products and services worldwide.
Modules
Compulsary classes: Intelligent Sensing and Reasoning and through Machine Learning, Neural Networks and Deep Learning, Reasoning and Deep Learning, Digital Signal Processing Principles, Big Data Technologies, Machine Learning for Data Analytics, Assignment and Professional Studies, MSc Project. Elective Classes: One to be chosen from - Image and Video Processing, Information Access and Mining
Entry requirements
Normally a first or second-class Honours degree, or equivalent overseas qualification, in electronic or electrical engineering, or computer science, from a recognised academic institution. Highly-qualified candidates from other relevant engineering or science-related disciplines may be considered.
Fees and funding
Tuition fees
| Scotland | £9250 | Year 1 |
| England | £9250 | Year 1 |
| Northern Ireland | £9250 | Year 1 |
| Wales | £9250 | Year 1 |
| International | £23050 | Year 1 |
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
For information on tuition fees, additional costs and funding for this programme, please view the programme details on the University of Strathclyde website.
Sponsorship information
https://www.strath.ac.uk/studywithus/scholarships/
Provider information
University of Strathclyde
McCance Building
16 Richmond Street
Glasgow
G1 1XQ