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Integrated Machine Learning Systems MSc

London, Bloomsbury

This MSc programme teaches how to engineer the machine learning systems that will form the basis of our economies, society and industry in the next few decades. It offers students the know-how necessary to pursue a wide variety of careers in the general field of integrated machine learning systems engineering in start-ups, well-established companies, or indeed research.

UK students International students
Study mode
UK tuition fees (2024/25)
£19,300
£9,650
Programme also available on a modular (flexible) basis.
Overseas tuition fees (2024/25)
£37,500
£18,750
Programme also available on a modular (flexible) basis.
Duration
1 calendar year
2 calendar years
5 calendar years
Programme starts
September 2024
Applications accepted
Applicants who require a visa: 16 Oct 2023 – 05 Apr 2024

Applications closed

Applicants who do not require a visa: 16 Oct 2023 – 30 Aug 2024
Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

A minimum of an upper second-class Bachelor's degree in electronic and electrical engineering, computer science, and related fields from a UK university or an overseas qualification of an equivalent standard. Basic knowledge (e.g. at UK 2:1 standard in relevant undergraduate-standard modules) of programming languages (such as C, C++, Python, Java, or similar) is required. Basic knowledge of mathematics (e.g. at UK 2:1 standard in relevant undergraduate-standard modules) is also required in algebra, analysis, probability, or statistics. Applicants must show an interest in developing thinking and problem-solving skills.

The English language level for this programme is: Level 1

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

Students will learn about the principles of data acquisition including the sensors and devices used to capture the data; the principles of data analysis; machine learning technology; and the infrastructure used to transport, store, secure, and process data. Students will therefore also learn how to put together integrated systems that can acquire, process and analyse data.

Who this course is for

The MSc is suited to students that desire to further develop their knowledge, know-how, and skills in machine learning technology.

The MSc is also suited to students that desire to pursue an industrial career in the general area of machine learning systems or that desire to pursue a research or academic career.

Read about what it takes to study for a Master's at UCL

What this course will give you

Our Integrated Machine Learning Systems MSc programme offers students a holistic view about machine learning technology, encompassing both the principles and practice of data aquisition, data analysis, and the infrastructure used to transport, store, secure and process data.

This MSc programme also offers students a wide range of hardware, software, and system skills, allowing them to develop upcoming machine learning systems supporting our economies and societies.

The MSc is delivered by world-leading academics in their respective fields, and is supported by state-of-the-art facilities and laboratories at the Electronic and Electrical Engineering Department at UCL.

Read about what you'll get out of a graduate programme

The foundation of your career

Students will acquire a wide range of theoretical and practical knowledge and skills in the general area of integrated machine learning systems, including in data acquisition, data analysis, and the infrastructure used to transport, store, secure and process data.

In particular, students will be exposed both to the principles and practice of machine learning systems, including the hardware, software and network components underpinning such systems.

Students will therefore be well positioned to pursue a wide range of careers in industry or academia upon completion of this programme.

Employability

It is expected that this MSc will deliver professionals in the general field of integrated machine learning systems engineering that can be recruited by the burgeoning industry in the area, such as emerging start-ups or well-established companies that need to recruit engineers with the necessary skills to set-up systems to make sense of data.

It is also expected that this MSc will deliver researchers that are well positioned to continue further doctoral studies.

Networking

The EEE department is conveniently located in the heart of London and has deep industry connections, providing unique and invaluable opportunities to students. We collaborate with world-leading industries across most of our Masters provision. During your time with EEE, you will gain an excellent understanding of applying theory to practice, in the form of guest lectures, invited seminars, site visits and placements as well as our world-renowned academic team bringing their own industry experience to the table.

Teaching and learning

The programme will be delivered through a combination of formal lectures, seminars, laboratories, workshop sessions and independent or group work.

The MSc programme assesses students in a number of ways including exams, coursework, group work, dedicated exercises and a research dissertation.

The number of contact hours per week with academic staff will vary. But as a rough guideline students can expect 12 to 16 contact hours in a typical week, averaged across term, across all activities (lectures, labs, tutorials and workshops). In addition students will generally need to devote a similar amount of time each week to self-directed study (for instance reviewing taught material and completing coursework).

Modules

This MSc programme in Integrated Machine Learning Systems covers the technology, applications, and the state-of-the-art in machine learning systems engineering.

In particular, it covers a series of topics relevant for machine learning systems engineering including: 1) elements associated with the data acquisition processes; 2) elements associated with the data analysis, processing, and visualization processes; and 3) aspects associated with the infrastructure used to transport, process and secure the data.

The students will undertake a series of compulsory and optional modules covering:

  • The principles, technology, and applications of signal acquisition, compression, and processing systems;
  • The principles and practice of machine learning, including both basic and advanced machine learning algorithmic technology;
  • The state-of-the-art in data centres, networking, and computing technology necessary to set-up integrated machine learning systems;
  • The design, the development and the evaluation of secure computer systems & networks with a focus on security/privacy challenges in a "Big Data" world.
  • Emerging and cutting-edge topics in integrated machine learning systems engineering.

The students will also undertake a research dissertation in the area of integrated machine learning systems during the course of the programme.

Finally, all students are due to carry out a compulsory non-credit bearing Professional and Development Skills course covering research, writing and presentation skills.

This MSc Programme in Integrated Machine Learning Systems covers the technology, applications, and the state-of-the-art in machine learning systems engineering.

In particular, this MSc Programme will cover a series of topics relevant for machine learning systems engineering including: 1) elements associated with the data acquisition processes; 2) elements associated with the data analysis, processing, and visualization processes; and 3) aspects associated with the infrastructure used to transport, process, and secure the data.

The students will undertake a series of compulsory and optional modules covering:

  • The principles, technology, and applications of signal acquisition, compression, and processing systems;
  • The principles and practice of machine learning, including both basic and advanced machine learning algorithmic technology;
  • The state-of-the-art in data centres, networking, and computing technology necessary to set-up integrated machine learning systems;
  • The design, the development and the evaluation of secure computer systems & networks with a focus on security/privacy challenges in a "Big Data" world.
  • Emerging and cutting-edge topics in integrated machine learning systems engineering.

The students will also undertake a research dissertation in the area of integrated machine learning systems during the course of the programme.

Finally, all students are due to carry out a compulsory non-credit bearing Professional and Development Skills course covering research, writing, and presentation skills.

This MSc Programme in Integrated Machine Learning Systems covers the technology, applications, and the state-of-the-art in machine learning systems engineering.

In particular, this MSc Programme will cover a series of topics relevant for machine learning systems engineering including: 1) elements associated with the data acquisition processes; 2) elements associated with the data analysis, processing, and visualization processes; and 3) aspects associated with the infrastructure used to transport, process, and secure the data.

The students will undertake a series of compulsory and optional modules covering:

  • The principles, technology, and applications of signal acquisition, compression, and processing systems
  • The principles and practice of machine learning, including both basic and advanced machine learning algorithmic technology;
  • The state-of-the-art in data centres, networking, and computing technology necessary to set-up integrated machine learning systems;
  • The design, the development and the evaluation of secure computer systems & networks with a focus on security/privacy challenges in a "Big Data" world.
  • Emerging and cutting-edge topics in integrated machine learning systems engineering

The students will also undertake a research dissertation in the area of integrated machine learning systems during the course of the programme.

Finally, all students are due to carry out a compulsory non-credit bearing Professional and Development Skills course covering research, writing, and presentation skills.

Compulsory modules









Optional modules






Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

The programme encompasses 180 credits. Students undertake six compulsory modules, two optional modules, a compulsory dissertation, and a compulsory non-credit bearing Professional Development Skills module. Upon successful completion of 180 credits, you will be awarded an MSc in Integrated Machine Learning Systems.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk. Further information can also be obtained from the UCL Student Support and Wellbeing team.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2024/25) £19,300 £9,650
Tuition fees (2024/25) £37,500 £18,750

Programme also available on a modular (flexible) basis.

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees.

Additional costs

The students are expected to have their own computer/laptop, in order to carry out independent study and programming assignments. Average laptop prices can range from £300-1000.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

The Institution of Engineering and Technology (IET) awards competitive scholarships for postgraduate study, for details visit www.theiet.org

Please visit the UCL Electronic and Electrical Engineering Scholarships website for more information on funding.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

See all the ways you can fund your studies

Next steps

There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees.

When we assess your application we would like to learn:

  • why you want to study Integrated Machine Learning Systems at graduate level
  • why you want to study Integrated Machine Learning Systems at UCL
  • what particularly attracts you to the chosen programme
  • how your academic and professional background meets the demands of this challenging programme
  • where you would like to go professionally with your degree.

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

The MSc programme is accessible to students with a minimum of an upper second-class Bachelor's degree in Electronic and Electrical Engineering, Computer Science, Mathematics, Statistics and related fields from a UK university of an overseas qualification of an equivalent standard.

Knowledge in programming languages is required. Basic knowledge in mathematics is required in algebra, analysis, probability or statistics. Standard UCL English Language requirements are also required.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Apply for this course

Got questions? Get in touch

Electronic and Electrical Engineering
Electronic and Electrical Engineering

eee-msc-admin@ucl.ac.uk

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