Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
Study Details: 12 months full-time
Machine learning and deep neural networks are at the heart of today’s technological revolution, driving innovation across nearly every sector – from healthcare and finance to robotics, transportation and the creative industries. This MSc is designed to equip you with the applied, industry-relevant expertise and practical skills needed to capitalise in the dynamic and fast-growing intelligent and smart systems domains.
Delivered jointly by the Departments of Electronic & Electrical Engineering (EEE) and Computer & Information Sciences the course offers a truly interdisciplinary learning experience. You’ll benefit from the combined strengths of both departments—gaining insights from leading academics in autonomous and intelligent control, machine learning, deep neural networks, data analytics and software engineering.
Through a blend of theoretical study and hands-on learning, you’ll develop a deep understanding of how intelligent systems are designed, built, and deployed. You’ll also engage with real-world challenges and industry case studies, learning to use the programming languages and engineering tools that drive innovation in today’s products and services.
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.
Graduates of this MSc will be equipped with the advanced technical and analytical skills required to thrive in a wide range of industries and roles from healthcare, finance and retail to the environment and transportation.
Potential industry career paths include:
Machine Learning Engineer – designing and deploying machine learning models for applications in finance, healthcare or retail
Deep Learning Specialist – developing advanced neural network architectures to support image recognition, natural language processing, and autonomous systems
AI Software Developer – building intelligent software solutions to support fraud detection, customer risk profiling in the finance sector
Data Scientist – extracting insights from complex datasets using machine learning techniques, to support medical diagnostics
AI Product Manager – leading the development of AI-powered products, bridging technical teams and business strategy
Automation Engineer – optimising industrial processing with AL to deliver enhanced performance and cost savings
Core modules:
Intelligent Sensing & Reasoning through Machine Learning (10 credits)
Neural Networks & Deep Learning (10 credits)
Machine Learning for Data Analytics (20 credits)
Assignment & Professional Studies (20 credits)
Digital Signal Processing Principles (20 credits)
Big Data Technologies (20 credits)
Optional modules:
Image & Video Processing (20 credits)
Information Access & Mining (20 credits)
The place of useful learning The University of Strathclyde is a leading international technological university located in the heart of Glasgow – one ...
