London, Bloomsbury
This is the programme information for 2025 entryIf you require details of the previous year's programme, Integrated Machine Learning Systems MSc (2024), click here
Join us on this one-year MSc for a full immersion into principles of data acquisition, analysis, security, and infrastructure. You will develop the expertise to excel in integrated machine learning systems engineering across start-ups, established companies, and research institutions.
UK studentsInternational students Study modeUK tuition fees (2025/26) £20,500£10,250Programme also available on a modular (flexible) basis. Overseas tuition fees (2025/26) £39,800£19,900Programme also available on a modular (flexible) basis.Duration1 calendar year 2 calendar years 5 calendar yearsProgramme startsSeptember 2025Applications accepted Applicants who require a visa:14 Oct 2024 – 04 Apr 2025 Applications close at 5pm UK timeApplications open
Applicants who do not require a visa:14 Oct 2024 – 29 Aug 2025 Applications close at 5pm UK timeApplications open
Apply for this courseEntry requirementsA 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 qualificationsCountry-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 degreeMachine learning is revolutionising technology and industries.
This one-year MSc offers a comprehensive understanding of integrated machine learning systems, from data acquisition and analysis to infrastructure, storage, and security.
You’ll gain both hardware and software skills essential for developing advanced systems that support economies and societies.
Designed for aspiring engineers and data scientists, the programme leverages UCL’s world-leading academics and state-of-the-art facilities at UCL Electronic and Electrical Engineering. This includes a dedicated Printed Circuit Board Facility, nanoscale processing and characterisation laboratories, low temperature quantum measurement labs, and well-equipped photonic and optical communication test laboratories.
You'll work alongside top researchers and industry experts, staying current with the latest developments. Access to guest lectures on topics such as privacy and security will further enhance your learning.
Graduates will be prepared for diverse roles in tech firms, established companies, or academic research, driving innovation in the dynamic field of machine learning systems.
Who this course is forThe MSc is ideal if you are looking to further develop your knowledge, know-how, and skills in machine learning technology.
It is particularly suited to those aiming to pursue an industrial career in the general area of machine learning systems or go on to a career in academic research.
Read about what it takes to study for a Master's at UCL What this course will give youThis programme offers you the following benefits and opportunities:
A postgraduate degree from a top-ranked university. UCL is consistently ranked among the best universities globally (ranked 9th in the latest QS World University Rankings 2025), providing you with a prestigious qualification that is highly regarded by employers worldwide. Benefit from state-of-the-art facilities and laboratories that support your learning and research.Gain a comprehensive understanding of machine learning technology, covering both principles and practical applications.Develop essential hardware, software, and system skills to engineer advanced machine learning systems.The course is continuously updated to reflect the rapid changes in the field.Study and network with renowned academics and experts at UCL Electronic & Electrical Engineering, a Department ranked 5th in the UK (QS World University Rankings by Subject 2024). Study in the world's best city for university students (QS Best Student Cities 2024). UCL’s Bloomsbury campus is in the heart of a London district famous for its cultural and educational institutions. Read about what you'll get out of a graduate programmeMaking an impact
Case study: Data paints a pictureOur partnership with the National Gallery is using cutting edge data science, machine learning and digital signal processing technology tools to support art conservation of Old Masters paintings.
The foundation of your careerThis programme provides you with comprehensive knowledge and practical skills in integrated machine learning systems, preparing you for a range of possible careers in industry or academia.
As the Programme Director, I like the quite unique point of view of this programme integrating all phases of Machine Learning Systems, fundamental to solving the interdisciplinary challenges our world is facing.
Dr Francesca Boem
MSc Integrated Machine Learning Systems
Find out more about Dr Boem's researchEmployabilityThe MSc Integrated Machine Learning Systems programme prepares you for dynamic careers in industries such as technology, finance, healthcare, and manufacturing. You will gain comprehensive expertise in both theoretical and practical aspects of machine learning, including data acquisition, analysis, and system infrastructure.
Graduates are equipped to excel in roles within startups, established enterprises, consulting and research institutions, contributing to pioneering projects and advancements in machine learning.
Graduates of this programme have gone on to work at such as DeepMind, IBM and Klaki. Others have used their solid foundation to pursue doctoral studies at UCL and further afield.
NetworkingYou’ll have regular opportunities to connect, collaborate, and build professional contacts as part of your Master’s programme.
Benefit from UCL’s central location in the heart of London, offering rich industry connections and opportunities.Whether you're advancing your career or transitioning from industry, tap into our extensive connections, with opportunities for site visits, placements, and collaborations with world-leading companies.Access exclusive industry events, including guest lectures with leading professionals.Participate in site visits and placements with world-leading industries.Engage with our world-renowned academic team and leverage their extensive industry experience.Work with leading professionals through invited seminars and collaborative projects.If you’re interested in entrepreneurship, connect with like-minded innovators and successful entrepreneurs through UCL’s innovation hubs and startup incubators.Teaching and learningThis MSc is delivered through a combination of formal lectures, seminars, laboratories, workshop sessions and independent or group work, which frequently draw upon real-life industry case studies.
You will be assessed via exams, coursework, group work, dedicated exercises and a research dissertation.
This is a full-time course, which means students should expect a working schedule of approximately 35 hours a week divided between contact hours and self-directed learning. The exact number of contact hours and composition varies throughout the term depending on the module choices of the student. Full-time students can expect their weekly schedule to include approximately 12 to 16 contact hours.
ModulesThis 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.
You 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.You will also undertake a research dissertation in the area of integrated machine learning systems during the course of the programme.
Finally, all students 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.
You 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.You will also undertake a research dissertation in the area of integrated machine learning systems during the course of the programme.
Finally, all students 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.
You will undertake a series of compulsory and optional modules covering:
The principles, technology, and applications of signal acquisition, compression, and processing systemsThe 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 engineeringYou will also undertake a research dissertation in the area of integrated machine learning systems during the course of the programme.
Finally, all students carry out a compulsory non-credit bearing Professional and Development Skills course covering research, writing, and presentation skills.
Compulsory modules Applied Machine Learning Systems I (MLS-1) Applied Machine Learning Systems II (MLS-II) Data Acquisition and Processing Systems (DPS) Cloud, Data Centres and Edge-Computing Security and Privacy Emerging Topics in Integrated Machine Learning Systems Research Project Optional modules Introduction to Internet Protocol Networks Internet of Things Deep Learning for Natural Language Processing Entrepreneurship: Theory and PracticePlease 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.
AccessibilityDetails of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support and Wellbeing Services team.
Where you'll study
UCL Electronic and Electrical Engineering’s facilities feature a variety of test equipment, including soldering stations, microscopes, and reflow ovens. Workstations offer test software, oscilloscopes, waveform generators, and digital multimeters. We provide 3D printers and a benchtop laser cutter for rapid prototyping of mechatronic designs. Our PCB Facility, staffed by experts, produces PCBs like RF, multilayer, and flexible circuits, using CNC machines, electroplating, laser ablation, and etching equipment. The department includes a computer lab and CPU/GPU servers. Research labs feature cleanrooms, nanoscale labs, quantum measurement labs, an anechoic chamber, and photonic and optical communication labs, supporting final-year projects and advanced research.
Find out more Visit us All open days and events3 December 2024Online - Open day
Graduate Open Events: Where can a UCL Engineering degree take you - Alumni Perspectives18:00—19:00
Where can a UCL Engineering degree take you? Join us for a panel and Q&A event with UCL Engineering alumni. You'll learn what you can expect from postgraduate study at UCL Engineering and get application advice from previous students! This is an opportunity for all applicants to hear personal experiences of studying with us, but may be most relevant to those applying from the USA, Latin and South America.
5 December 2024Online - Open day
Graduate Open Events: Where can a UCL Engineering degree take you - Alumni Perspectives12:00—13:00
Where can a UCL Engineering degree take you? Join us for a panel and Q&A event with UCL Engineering alumni. You'll learn what you can expect from postgraduate study at UCL Engineering and get application advice from previous students! This is an opportunity for all applicants to hear personal experiences of studying with us, but may be most relevant to those applying from the USA, Latin and South America.
Fees and fundingFees for this course UK studentsInternational studentsFee description Full-time Part-timeTuition fees (2025/26) £20,500£10,250 Tuition fees (2025/26) £39,800£19,900Programme 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 costsFor Full-time and Part-time offer holders a fee deposit will be charged at 10% of the first year fee.
For flexible/modular offer holders a £500 fee deposit will be charged.
Further information can be found in the Tuition fee deposits section on this page: Tuition fees.
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.
UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £114.50. This price was published by TfL in 2024. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.
Funding your studiesThe 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 studiesNext stepsThere is an application processing fee for this programme of £90 for online 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 levelwhy you want to study Integrated Machine Learning Systems at UCLwhat particularly attracts you to the chosen programmehow your academic and professional background meets the demands of this challenging programmewhere 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.
This programme requires two references. Further information regarding references can be found on this Selecting your references page. Choose your programmePlease read the Application Guidance before proceeding with your application.
Apply for this courseGot questions? Get in touch
Electronic and Electrical Engineering eee-msc-admin@ucl.ac.uk
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