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Artificial Intelligence and Data Engineering MSc

London, Bloomsbury

UK students International students

Study mode

Full-time

UK tuition fees (2024/25)

£19,300

Overseas tuition fees (2024/25)

£37,500

Duration

1 calendar year

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 UK Bachelor's degree (or international qualification of an equivalent standard) in computer science, computing, or software engineering including a good background in data systems, artificial intelligence, and mathematics. Relevant work experience may also be considered.

The English language level for this programme is: Level 2

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

There is a high demand for graduates with combined expertise in machine learning and software engineering to fill positions advertised as Artificial Intelligence Engineer, Machine Learning Engineer or Data Engineer.

This new MSc in Artificial Intelligence and Data Engineering responds to this demand by integrating modules from our highly regarded MSc in Software Systems Engineering and from our Master’s in machine learning, together with newly created modules in data engineering.

The programme covers foundations and practices for all software engineering activities needed for the design, coding, testing, deployment and evolution of large-scale, data-intensive systems. It also includes electives in machine learning and data science.

The programme includes a substantial engineering or research project where you will apply the knowledge and skills developed throughout the year to real-world problems. Most of our Master’s engineering projects are in collaboration with our industry partners through the Department’s leading Industry Exchange Network (IXN). Research projects are with world experts in the fields of software engineering and Artificial Intelligence.

Who this course is for

The programme is designed for students with a background and a strong interest in software engineering.

If your primary interest is in data science and machine learning rather than the engineering of complex software systems that use Machine Learning, our other Artificial Intelligence and Machine Learning-related MSc programmes may be more suitable.

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

What this course will give you

UCL is ranked 9th globally in the latest QS World University Rankings (2024), giving you an exciting opportunity to study at one of the world’s best universities.

UCL Computer Science is recognised as a world leader in teaching and research. The department was ranked first in England and second in the UK for research power in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2021.) You will learn from leading experts at the forefront of computer science innovation.

Our taught postgraduate programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries. Graduates of our programmes are highly valued as a result of the department's strong international reputation, strong links with industry, and ideal location close to the City of London.

The programme team takes an experimental approach to our subject, enjoys the challenge and opportunity of entrepreneurial partnerships, and places a high value on our extensive range of industrial collaborations.

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

The foundation of your career

This programme route is intended to run for the first time in September 2024, therefore, there are no alumni yet. However, Computer Science alumni have been employed at global companies, sometimes by the companies they have engaged within the context of their final project/dissertation, whilst others have gone on to pursue further study or a career in academia.

Significant attention has been received from various industrial partners who eagerly seek to recruit graduates from the esteemed programme. Their enthusiastic support and endorsement acknowledge the exceptional skills and qualifications possessed by our graduates in the dynamic fields of Artificial Intelligence and Data Engineering.

The strong demand for graduates in the current job market is further highlighted through collaborative engagement with industrial partners. The exceptional value and expertise provided by the programme are recognised by the industry, positioning our graduates as highly sought-after candidates for a wide range of employment opportunities.

Employability

Many sectors rely on large Artificial Intelligence or data-driven software systems, and you will gain exposure to some of these throughout the programme due to UCL’s strong industry ties. You will acquire a strong skillset in the many aspects of large software systems engineering during this programme, enabling you to pursue a career as an Artificial Intelligence software engineer, Artificial Intelligence system engineer or general software engineer when you graduate.

The research-based curriculum promotes strong research skills, which you will develop through your final research project/dissertation; you will be well-equipped to undertake doctoral research in software engineering for large data-driven systems.

Networking

Networking is a crucial part of the programme that can greatly enhance your career prospects and professional development. During the programme, you have ample opportunity for networking with peers and members of academia and industry, particularly through collaborative project work and research seminars.

UCL also has a large number of clubs and societies which can be an effective way to connect with peers who share similar interests and career goals. London’s Tech Scene is vibrant and has regular networking events.

Teaching and learning

The programme’s core curriculum is typically delivered through a combination of lectures, tutorials, and lab classes, as well as directed and self-directed learning supported by teaching materials and resources, published through each module’s online virtual learning environment. Each module employs a teaching strategy that aligns with and supports its intended learning outcomes.

You will be assessed through a range of methods across the programme, which will vary depending on any optional or elective module choices. The programme’s core curriculum is typically assessed by methods including coursework, lab work, individual and group projects, class tests, written examinations, oral assessments, and, in all cases, culminating in a final research project/dissertation.

Contact time takes a variety of forms, including lectures, seminars, tutorials, project supervisions, demonstrations, practical classes and workshops, visits, placements, office hours (where staff are available for consultation), email, videoconference, or other media, and situations where feedback on assessed work is given (one-to-one or in a group).

Each module has a credit value that indicates the total notional learning hours a learner will spend on average to achieve its learning outcomes. One credit is typically described as being equal to 10 hours of notional learning, which includes all contact time, self-directed study and assessment.

The contact time for each of your 15 credit taught modules will typically include 22-30 hours of teaching activity over the term of its delivery, with the balance then comprised of self-directed learning and working on your assessments. You will have ongoing contact with teaching staff via each module’s online discussion forum, which is typically used for discussing and clarifying concepts or assessment matters and will have the opportunity to access additional support via regular office hours with module leaders and programme directors.

Your research project/ dissertation module is 60 credits and will include regular contact with your project supervisor(s), who will guide and support you throughout your project. You will dedicate most of your time on this module to carrying out research in connection with your project and writing up your final report.

Modules

The Artificial Intelligence and Data Engineering MSc is a one-year programme.

In Term 1, you will study requirements for engineering and software architecture, which will introduce you to fundamental concepts and the latest techniques to develop your modelling skills and your ability to communicate requirements and architectures with clarity and precision to business stakeholders and software developers. You will learn applied technical details of deploying and maintaining data science applications and how to develop and write your own large-scale, state-of-the-art Machine Learning analyses. You will also learn about the theory and practical applications in Data Engineering and Machine Learning Ops, focusing on designing, developing and deploying high-throughput data science applications and pipelines in cloud environments. You will choose from a range of specialist optional topics, which may include introductory machine learning and supervised learning.

In Term 2, you will study validation and verification, which will cover not only the state-of-the-practice in validation and verification, but also the most significant trends, problems and results in validation and verification research. You will extend your knowledge of engineering for data analysis, be introduced to principles in designing and developing data science applications platforms, and learn the applied technical details of deploying and building data science applications. You will also learn about theories and principles of scaled data software engineering with a focus on designing and developing real-world high throughput data science applications and pipelines. It also offers hands-on experience in deploying state-of-the-art development platforms. You will choose from selected optional topics, which may include data science and applied deep learning. You will also begin preparation for your final research project/ dissertation.

In Term 3, you will primarily focus on your final research project/dissertation (either group or individual) and any examinations that take place in the main examination period.

Compulsory modules

Requirements Engineering and Software Architecture

Validation and Verification

Software Development Practice

Professional Practice

Engineering for Data Analysis 1

Engineering for Data Analysis 2

MSc Software Systems Engineering Group Project

MSc Artificial Intelligence and Data Engineering Research Project

Optional modules

Supervised Learning

Introduction to Machine Learning

Data Science

Applied Deep Learning

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.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Artificial Intelligence and Data Engineering.

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.

Visit us

All open days and events

Online - Open day

Graduate Open Events: Department of Computer Science

Join us for a live online information session to hear from Computer Science staff. We will cover areas such as the general admission process, careers support, and industry links/placements. There will also be an opportunity for you to ask staff and current students any questions you may have. Two sessions will run for this event. These sessions are the same and are repeated to cater to people in different time zones.

Watch on demand event

Fees and funding

Fees for this course

UK students International students

Fee description	Full-time
Tuition fees (2024/25)	£19,300
Tuition fees (2024/25)	£37,500

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

Students will require a modern computer (PC or Mac) with minimum specifications 8GB RAM and 500GB SSD storage. A computer with the stated specifications is estimated to cost £500 or greater.

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

For more information about funding opportunities for UCL Computer Science taught postgraduate programmes, please see the department's scholarships webpage.

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

: UCL East London Scholarship

Deadline: 20 June 2024

Value: Tuition fees plus £15,700 stipend ()

Criteria Based on financial need

Eligibility: UK

UCL Friends & Alumni Association scholarship for Machine Learning

Deadline: 3 June 2024

Value: $20,000 (1 year)

Criteria Based on both academic merit and financial need

Eligibility: EU, Overseas

Next steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

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.

Your personal statement should include:

why you want to study Artificial Intelligence and Data Engineering at taught postgraduate level.
why you want to study Artificial Intelligence and Data Engineering at UCL.
what particularly attracts you to this programme.
how your academic and professional background meets the demands of this programme. What programming experience you have.
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. Your application will be judged entirely on the evidence you provide.

Due to competition for places on this programme, no late applications will be considered. Students with visa requirements or applying for scholarships are advised to apply early.

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 programme

Please read the Application Guidance before proceeding with your application.