The University of Strathclyde is inviting applications for its MSc Machine learning & Deep Learning course

The University of Strathclyde, Glasgow is inviting applications for its MSc Machine learning & Deep Learning course starting in September 2022.

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.

The 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.

You’ll complete six classes over two semesters comprising compulsory and elective taught classes. These are followed by a three-month research project in a chosen area.

You’ll also have the opportunity to complete the project through the university’s competitive MSc industrial internships. These are offered in collaboration with selected industry partners.


Eligibility- Normally a first-class or second-class honours degree (or international equivalent) in electronic or electrical engineering, or computer science.

Highly-qualified candidates from other relevant engineering or science-related disciplines may be considered.


Fee- £23,050 for international students for 2022/23


Scholarship – a range of scholarships starting from £3,450 will be available for this programme


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