Applied Machine Learning

Gain the skills to design, implement and evaluate machine learning systems.

Key information

Duration: 1 year full-time
Start dateOctober 2021
Location: South Kensington
ECTS: 90 credits
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Overview

During this course, you will focus on applying machine learning to electrical engineering. Applications include robotics, computer vision bio-inspired learning, communication and signal processing.

This course is perfect if you’re interested in developing real-world systems. These will involve signals, sensors and hardware, such as robots or communication devices.

Address the challenge of how automated systems can learn from signals and data as they operate in real environments.

Learn through specialised modules including a specialised computer laboratory module. These allow you to develop practical skills with industrial input and your own individual project.

  • Learn the theoretical basis for machine learning systems, design methods and algorithms for modelling real systems
  • Equip yourself to a range of careers. These could involve the design, modelling, analysis and control of intelligent signal and data processing
  • Develop advanced knowledge of machine and deep learning in engineering
  • Gain skills that enable you to continue your studies to PhD level

Through the course, you will learn from field-leading staff. You will gain a critical awareness of current issues, research and their applications. Applying different methodologies, you will tackle complex issues systematically and creatively.

Structure

Modules shown are for the current academic year and are subject to change depending on your year of entry.

There are limited circumstances in which we may need to make changes to or in relation to our courses. See what changes we may make and how we will tell you about them.

Find out more about potential changes

Structure

Core modules

You will study all the modules below. This includes a substantial individual project.

  • Machine Learning
  • Deep Learning
  • Laboratory in Applied Machine Learning
  • Individual Project in Applied Machine Learning

Optional modules

Optional modules allow you to broaden your experience of machine learning applications.

The following is an indicative list of the modules you can expect to choose from.

  • Artificial Intelligence
  • Digital Signal Processing and Digital Filters
  • Human-Centered Robotics
  • Pattern Recognition
  • Probability and Stochastic Processes
  • Topics in Large Dimensional Data Processing
  • Adaptive Signal Processing and Machine Intelligence
  • High Performance Computing for Engineers
  • Selected Topics in Computer Vision
  • Self-Organising Multi-Agent Systems
  • Speech Processing

These modules are subject to change for your year of entry.

Individual Project

This project is an opportunity for you to demonstrate independence and originality.

You will plan and organise a large project over a long period, applying techniques you have learned. It’s a chance to develop a significant machine learning approach in the electrical and electronic engineering domain.

The idea could be your own or come from a member of staff (possibly in conjunction with industry), or a combination of the two.

Teaching and assessment

Teaching

  • Lectures
  • Seminars
  • Tutorials
  • Laboratory-based teaching and learning
  • Independent study option (one-to-one study of a topic under the supervision of an advisor)
  • Coursework
  • Individual and group projects

Assessment

Summative assessment

  • Written exams
  • Coursework
  • Computer laboratory work
  • Written reports
  • Oral presentation

Formative assessment

  • Case studies
  • programming activities
  • group work 

Overall workload

The expected total study time is 2,250 hours per year.

Your overall workload consists of face-to-face sessions and independent learning. Contact hours may vary according to the modules you choose.

At Imperial, each ECTS credit taken equates to an expected total study time of 25 hours.

Entry requirements

We welcome students from all over the world and consider all applicants on an individual basis.

Entry requirements

Minimum academic requirement

Our minimum requirement is a first-class degree in electrical/electronic engineering, or a related subject with a substantial electrical/electronic engineering component.

When an applicant does not meet the entry requirement, but has at least three years of relevant work experience, exceptionally the Postgraduate Admissions Tutor may make a special case for admission.

International qualifications

We also accept a wide variety of international qualifications.

The academic requirement above is for applicants who hold or who are working towards a UK qualification.

For guidance see our Country Index though please note that the standards listed here are the minimum for entry to the College, and not specifically this Department.

If you have any questions about admissions and the standard required for the qualification you hold or are currently studying then please contact the relevant admissions team.

English language requirement (all applicants)

All candidates must demonstrate a minimum level of English language proficiency for admission to the College.

For admission to this course, you must achieve the higher College requirement in the appropriate English language qualification. For details of the minimum grades required to achieve this requirement, please see the English language requirements for postgraduate applicants.

How to apply

How to apply

Making an application

Apply online

All applicants must apply online.

Visit our Admissions website for details on the application process.

You can submit one application form per year of entry. You can usually choose up to two courses.

Application fee

For 2021–22 entry, we are introducing a pilot application fee for our Master's courses. This helps cover some of the administrative and staffing costs associated with processing the large volume of applications we receive.

This fee will be £80 per application and not per course. 

We will waive the fee for any applicant – Home or Overseas – who demonstrates that they are experiencing financial hardship.

Find out more about the application fee and waiver

The fee for MBA applications to Imperial College Business School is £135. There is no application processing fee for other postgraduate courses such as PhDs.

Application deadline

The Department of Electrical and Electronic Engineering will accept applications for this course until 30 June 2020.

ATAS certificate

An ATAS certificate is not required for overseas students applying for this course.

Tuition fees and funding

The level of tuition fees you pay is based on your fee status, which we assess based on UK government legislation.

For more information on the funding opportunities that are available, please visit our Fees and Funding website.

Tuition fees

Home rate of tuition

2021 entry

£18,500 per year

Fees are charged by year of entry to the College and not year of study.

Except where otherwise indicated, the fees for students on courses lasting more than one year will increase annually by an amount linked to inflation, including for part-time students on modular programmes. The measure of inflation used will be the Retail Price Index (RPI) value in the April of the calendar year in which the academic session starts e.g. the RPI value in April 2021 will apply to fees for the academic year 2021–2022.

EU/EEA students

Students from the EU, other EEA country and/or Switzerland starting a course on or after 1 August 2021 will no longer be eligible for the Home rate of tuition, and so will be charged the Overseas fee. Please note, this does not apply to Irish students or students with Citizens Rights benefitting from Citizens’ Rights under the EU Withdrawal Agreement, EEA EFTA Separation Agreement or Swiss Citizens’ Rights Agreement respectively.

For regular updates for EU students, please see our Imperial and the EU webpages.

Overseas rate of tuition

2021 entry

£34,750 per year

Fees are charged by year of entry to the College and not year of study.

Except where otherwise indicated, the fees for students on courses lasting more than one year will increase annually by an amount linked to inflation, including for part-time students on modular programmes. The measure of inflation used will be the Retail Price Index (RPI) value in the April of the calendar year in which the academic session starts e.g. the RPI value in April 2021 will apply to fees for the academic year 2021–2022.

EU/EEA students

Students from the EU, other EEA country and/or Switzerland starting a course on or after 1 August 2021 will no longer be eligible for the Home rate of tuition, and so will be charged the Overseas fee. Please note, this does not apply to Irish students or students with Citizens Rights benefitting from Citizens’ Rights under the EU Withdrawal Agreement, EEA EFTA Separation Agreement or Swiss Citizens’ Rights Agreement respectively.

For regular updates for EU students, please see our Imperial and the EU webpages.

Postgraduate Master's loan

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 2020-21 entry, the maximum amount was of £11,222. The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.

Scholarships

We offer a range of scholarships for postgraduate students to support you through your studies. Find out more about our scholarships to see what you might be eligible for.

There are a number of external organisations also offer awards for Imperial students, find out more about non-Imperial scholarships.

Accommodation and living costs

Living costs, including accommodation, are not included in your tuition fees.

You can compare costs across our different accommodation options on our Accommodation website.

A rough guide to what you might expect to spend to live in reasonable comfort in London is available on our Fees and Funding website.

Further information

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