Applied Machine Learning
Learn how to design, implement and evaluate machine learning systems.
Learn how to design, implement and evaluate machine learning systems
Develop practical skills with industrial input
Work alongside internationally-leading experts in machine learning
Course key facts
Qualification
MSc
Duration
1 year
Start date
September 2025
Study mode
Full-time
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Fees
£23,400 Home
£43,800 Overseas
Delivered by
Location
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South Kensington
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Minimum entry standard
First class Honours (minimum of 75% overall) in electrical/electronic engineering or a related subject with a substantial electrical/electronic engineering component
Course overview
Explore the processes used to develop real-world systems that involve signals, sensors and hardware, such as robots or mobile phones.
Through lectures, tutorials and labs, you'll delve into the theory, practical knowledge and skills that underpin machine learning. You'll then apply this knowledge to a range of electrical engineering domains.
Specialist modules will give you the opportunity to improve your understanding of specific machine learning applications, including AI, computer vision, robotics and signal processing.
You'll also complete an individual research project, which encourages you to develop your own ideas towards a machine learning approach.
A wide range of industries value the skills you have the opportunity to gain on this course including telecommunications, energy, healthcare and logistics. You also have the opportunity to go into further research.
Structure
This page is updated regularly to reflect the latest version of the curriculum. However, this information is subject to change.
Find out more about potential course changes.
Please note: it may not always be possible to take specific combinations of modules due to timetabling conflicts. For confirmation, please check with the relevant department.
You'll take all of these core modules, including a substantial individual project to showcase your machine learning knowledge.
Core modules
Examine the theory and practice of modern machine learning methods, and learn how machine learning helps computers extract information automatically from data.
Develop skills essential for carrying out group research projects in deep learning, applied to electrical and electronic engineering problems.
Focus on deep neural network based learning and learn how it impacts our understanding of intelligence and contributes to the practical design of intelligent machines.
Work in a small group to research, design and build a novel hardware device that makes intelligent decisions.
You’ll also choose six optional modules.
Optional modules
Develop further insight into the applicability of modern methods for spectral estimation and machine intelligence techniques such as dimensionality reduction and neural and deep networks.
Discover the concepts, basic formulations and applications of pattern recognition.
Assess the fundamental digital image processing methods that stem from a signal processing approach.
Gain an insight into key artificial intelligence concepts and the analysis of algorithms.
Explore finite-dimensional optimisation theory and learn to formulate optimisation problems, design computer algorithms for finding minima and maxima and modify algorithms in standard computer packages.
Gain the analytical skills required to study random phenomena in engineering systems and learn how to set up probabilistic models for engineering problems.
Become acquainted with the signal processing and statistical techniques that are used in processing speech signals and understand how they are used.
Understand the challenges involved with engineering ever more complex socio-technical and cyber-physical systems to support and enhance a “digital society”.
Broaden your knowledge of advanced modern control methodologies and explore topics including Kalman filtering and tracking, fault detection and isolation, and linear matrix inequalities.
Become familiar with the theory and design of algorithms to acquire and process large dimensional data arising in areas such as finance and the internet.
Advance your understanding of wavelet theory and discover how wavelets extract essential information in a fast and effective way.
You’ll complete an individual research project, which is a chance for you to develop a significant machine learning approach in the electrical and electronic engineering space.
You are encouraged to bring original thinking to a research area of interest to you.
Teaching and assessment
Balance of teaching and learning
Key
- Lectures and lab work
- Independent study
- Research project
- 20% Lectures and lab work
- 36% Independent study
- 44% Research project
Teaching and learning methods
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Virtual learning environment
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Lectures
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Seminars
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Tutorials
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Laboratory work
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Independent study
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Individual and group projects
Balance of assessment
Key
- Coursework
- Examinations
- Practical
- 50% Coursework
- 40% Examinations
- 10% Practical
Assessment methods
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Coursework
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Examinations
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Practical
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Individual research project
Entry requirements
We consider all applicants on an individual basis, welcoming students from all over the world.
How to apply
Apply online
You can submit one application form per year of entry. You can choose up to two courses.
Application deadlines – Round 3 closes on Thursday 15 May 2025
We operate a staged admissions process with several application rounds throughout the year.
Apply by 23.59 (UK time) on the closing date of an application round, to ensure you receive a response on your application by the relevant decision date.
Application rounds
Round 1
- Applications open on Friday 27 September 2024
- Applications close on Thursday 16 January 2025
- Decision by Thursday 6 March 2025
Round 2
- Applications open on Friday 17 January 2025
- Applications close on Thursday 27 March 2025
- Decision by Thursday 1 May 2025
Round 3
- Applications open on Friday 28 March 2025
- Applications close on Thursday 15 May 2025
- Decision by Thursday 17 July 2025
There is no application fee for MRes courses, Postgraduate Certificates, Postgraduate Diplomas, or courses such as PhDs and EngDs.
If you are applying for a taught Master’s course, you will need to pay an application fee before submitting your application.
The fee applies per application and not per course.
- £80 for all taught Master's applications, excluding those to the Imperial College Business School.
- £100 for all MSc applications to the Imperial College Business School.
- £150 for all MBA applications to the Imperial College Business School.
If you are facing financial hardship and are unable to pay the application fee, we encourage you to apply for our application fee waiver.
Find out more about how to apply for a Master's course, including references and personal statements.
An ATAS certificate is not required for students applying for this course.
Fees and funding
Home fee
2025 entry
£23,400
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a Postgraduate Master’s Loan from the UK government, if you meet certain criteria.
For courses starting on or after 1 August 2024, the maximum amount is £12,471.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
Overseas fee
2025 entry
£43,800
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a Postgraduate Master’s Loan from the UK government, if you meet certain criteria.
For courses starting on or after 1 August 2024, the maximum amount is £12,471.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
How will studying at Imperial help my career?
Discover how electrical engineering can be applied to machine learning by developing real-world systems.
Prepare for careers in areas requiring intelligent signal and data processing design, analysis, and control.
Electrical and electronic engineering graduates at Imperial are highly sought after in a wide range of sectors.
These include robotics, computing and communications.
Further links
Contact the department
- Telephone: +44 (0)20 7594 3123
- Email: eee.pgadmissions@imperial.ac.uk
Course Director: Professor Krystian Mikolajczyk
Academic Lead: Dr Ad Spiers
Visit the Department of Electrical and Electronic Engineering website.
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Terms and conditions
There are some important pieces of information you should be aware of when applying to Imperial. These include key information about your tuition fees, funding, visas, accommodation and more.
You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.
Programme specifications