• Postgraduate taught
  • MSc

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

Minimum entry standard

  • First class Honours in electrical/electronic engineering or a related subject with a substantial electrical/electronic engineering component.

View full entry requirements

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. 

This course focuses on hands-on experience by designing and implementing machine learning on hardware devices. Working in a small group, you will research, design and build a novel hardware device for making intelligent decisions based on signals from various sensors. 

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.

You’ll also choose six optional modules.

The individual research project is the culmination of your postgraduate studies. You will carry out a piece of individual research which will  have some element of originality and scientific rigour.

The project will be in the area of your MSc, and it will require you to adopt analytical, computational and/or experimental methods. You will be supervised by staff who are experts in the topic area of the project.  Your project will be assessed by written report and a poster presentation.

Professional accreditation

Accredited by the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to fully meet the CEng registration educational requirements.

Our accreditation agreement with the Institution of Engineering and Technology is renewed every 5 years, and the current agreement runs between 2025 and 2029.

Teaching and assessment

Balance of teaching and learning

This is a general guide to how teaching and learning are usually balanced across this course. The methods used may change based on the modules you take.

Key

  • Lectures and lab work
  • Independent study
  • Research project

  • 20% Title 1 goes here
  • 36% Title 2 goes here
  • 44% Title 3 goes here

Teaching and learning methods

  • Blackboard virtual learning environment
    Virtual learning environment
  • Person at lectern giving speech
    Lectures
  • Seminars
  • Four students sitting in a tutorial
    Tutorials
  • Laboratory work
  • A person studying independently
    Independent study
  • Individual and group projects

Balance of assessment

This is an example of how assessments are usually divided, based on a typical pathway through the course. The actual breakdown may be different depending on the modules you choose.

Key

  • Coursework
  • Examinations
  • Practical

  • 50% Title 1 goes here
  • 40% Title 2 goes here
  • 10% Title 3 goes here

Assessment methods

  • Person completing coursework
    Coursework
  • A person completing a written exam
    Examinations
  • Checklist for a practical examination
    Practical
  • Individual research project
  • Poster project
    Poster presentations

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 2 closes on Wednesday 7 January 2026

Fees and funding

Home fee

2026 entry

£24,600

Overseas fee

2026 entry

£46,000

EEE MSc Studentships

Value per award

  • Will cover difference between Home and Overseas fees.

Who it's for

  • Prospective students of specific EEE MSc courses.
Find out more

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.

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.

Read our terms and conditions

You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.

Programme specifications