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Machine Learning and Deep Learning

UK

10

5

What will I learn?

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.

Which department am I in?

Electronic and Electrical Engineering

Study options

Full Time (1 year)

Tuition fees
£21,850.00 (US$ 26,358) per year
The fees shown are annual and may be subject to an increase each year. Additional fees applicable.

This is a fixed fee
Start date

Expected September 2023

Venue

University of Strathclyde

McCance Building,

16 Richmond Street,

Glasgow,

Glasgow, City Of,

G1 1XQ, Scotland

Entry requirements

For students from United States

Students need to have a minimum GPA of 3.0 or above on a 4.0 scale. Some courses may accept a lower GPA and will take into consideration your supporting documents. Applications are made directly to Strathclyde for postgraduate study. IELTS (Academic): 6.5 overall (no individual band less than 5.5).

For international students

Students need 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. IELTS (Academic): 6.5 overall (no individual band less than 5.5).

*There may be different IELTS requirements depending on your chosen course.

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