University Of Strathclyde Invites Applications For MSc Machine Learning & Deep Learning Course

Study in UK: International students who are classified as self-funded for fee-paying will be eligible for a £5,000 scholarship. The course will commence in September 2025.

University of Strathclyde, Glasgow has invited applications for the MSc Machine Learning & Deep Learning course. The program will commence in September 2025. The fee for international students is £31,100.

The course is designed for scientists and engineers who want to develop skills in deep neural network systems and machine learning to design related systems which can be used by the industry. The leading research centres and organisations worldwide are increasingly using Machine learning and deep neural network systems in a wide range of applications and products.

“Self-funded, international (non-EU) fee paying students starting this course full-time in September 2025 are eligible for a £5,000 scholarship, which will be automatically deducted from their tuition fees,” reads the University of Strathclyde statement.

Eligibility Criteria For MSc Machine Learning & Deep Learning Course

The following are the eligibility criteria:

• The candidates need to have a first-class or second-class honours degree in computer science or electronic or electrical engineering.
• Also, candidates from other relevant engineering or science disciplines who are highly qualified will be considered.
• They need to submit an IELTS (Academic) score of 6.5 with no band less than 5.5.

MSc Machine Learning & Deep Learning Course Details

The program focuses on state-of-the-art technologies for deep neural network systems and machine learning. The emphasis is on algorithms, architectures, and implementation with applications in various areas.

Department of Electronic & Electrical Engineering will administer the course and offer it jointly with the Department of Computer & Information Sciences. Students will develop their practical skills by working on industry-relevant projects.

“Interaction with industry is provided through the university's industrially engaged projects, teaching seminars and networking events. Companies such as Leonardo, Comcast (Sky), ORE Catapult, PNDC, Xilinx, Texas Instruments, MathWorks, NHS, Canon Medical Research and Varian Ltd are just a few examples of the industry partners students can engage with during their course,” added the university.

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