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Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)
Image from Computing (Artificial Intelligence and Machine Learning)

Master of Engineering (with Honours) - MEng (Hon)

Computing (Artificial Intelligence and Machine Learning)

Entry requirements

Here's what you will need to get a place on the Computing (Artificial Intelligence and Machine Learning) course at Imperial College London.

Select a qualification to see required grades

A level

A*,A*,A

Our minimum entry standard is A*A*A to A*AAA overall, to include: A* in Mathematics A*A in two further subjects or AAA in three further subjects ICT, Business Studies, General Studies and Critical Thinking are not accepted. Recommended subjects Computer Science Further Mathematics Physics Useful subjects Ancient language Biology Chemistry Economics Electronics English Literature History languages Law Philosophy Politics Psychology Recommended and useful subjects are those that the Department deems to be very useful knowledge foundations to undertake a computing degree at Imperial. The department may still consider applicants with other subject combinations. Students taking English exam board science A-levels will be required to pass the practical endorsement.

Course summary

What this course is about

UCAS code: G700

Here's what Imperial College London says about its Computing (Artificial Intelligence and Machine Learning) course.

Computing is a creative and wide-ranging subject that focuses on using sound underlying principles and logical thinking to design and build systems that really work.

You'll specialise in artificial intelligence and knowledge engineering, as well as machine learning and the development of computational and engineering models of complex cognitive and social behaviours.

In this course, you will learn how modern computer and communications systems function, and how they can be used and adapted to build the next generation of computing applications.

The core of this programme has been designed to give you an overview of computing. This includes an understanding of basic concepts and principles, the ability to appreciate and to adapt to changes in technology, and practical experience in applied computing.

A special emphasis of your studies will be on the fundamental principles underlying computing and on the engineering considerations involved in computing system design, implementation and usage. You will be introduced to computing architecture and hardware, and the software used to exploit them.

This course will also equip you with a strong background in discrete mathematics (logic, sets, relations and grammar), classical mathematics and statistics relevant to applications engineering and management.

Throughout the programme, you will attend laboratory and problem-solving classes, as well as completing project and design work. As the course progresses, you will study advanced techniques and modules; many of which draw on current research taking place in the Department.

At the end of your third year, you will gain valuable skills and experience by completing an industrial placement. Your study reaches Master's level in the final year, with a wide choice of optional modules and a substantial individual project on a subject of your choice.

Source: Imperial College London

Course details

Qualification

Master of Engineering (with Honours) - MEng (Hon)

Department

Computing

Location

Main Site | London

Duration

4 Years

Study mode

Full-time

Subjects

• Artificial intelligence

Start date

26 September 2026

Application deadline

14 January 2026

The modules you will study

We recommend reviewing our course page for the latest information regarding the curriculum (including core and optional modules) and course structure, as this information may be subject to periodic change.

Imperial College London reviews

(3.9)
Based on 99 reviews from Imperial College London's students and alumni
5 star
34%
4 star
32%
3 star
23%
2 star
7%
1 star
3%
All reviews

Showing 96 reviews

1st year student

SOOOO MANY CLUBS. Theyu2019re all free so many things to do and try out.

(5)

1 year ago

1st year student

London is alive thereu2019s lots to do and see which is nice! But it is all expensive!

(4)

1 year ago

1st year student

Iu2019m not sure on the support as I havenu2019t applied and looked but there is options. It is very expensive for the accommodation. The shops you have to be careful on what you buy a week. But that is London

(5)

1 year ago

1st year student

Each course has a wellbeing officer and mine is so nice! Thereu2019s a room to sleep in if needed as I have a health issue. Teachers are happy to explain things during a tutorial (where you can ask teacher anything and work with course mates)

(5)

1 year ago

1st year student

Library is very clean, only uni students can get it. The only problem is thereu2019s sometimes mice. My accommodation has 25 in a flat and the kitchen is disgusting! Iu2019m paying u00a3280 per week! Thereu2019s mould and Iu2019ve tried telling people to clean but I try and clean but it always gets ...

(3)

1 year ago

1st year student

Lecturers are generally really good. Some a lot better than the others. The structure is very good. I know whatu2019s next lecture and what to revise/write for next lecture. The only problem is some modules arenu2019t clear so I find YouTube a lot more helpful. You have to do a lot of your own work

(4)

1 year ago

National Student Survey (NSS) scores

The NSS is an annual survey where final-year students are asked to rate different aspects of their course and university experience.

Here you can see ratings from Imperial College London students who took the Computing (Artificial Intelligence and Machine Learning) course - or another course in the same subject area.

Computing

Select an option to see a detailed breakdown

How often does your course challenge you to achieve your best work?

94%

high

How good are teaching staff at explaining things?

93%

med

How often do teaching staff make the subject engaging?

83%

med

How often is the course intellectually stimulating?

96%

high

To what extent have you had the chance to bring together information and ideas from different topics?

85%

high

How well does your course introduce subjects and skills in a way that builds on what you have already learned?

91%

high

How well has your course developed your knowledge and skills that you think you will need for your future?

96%

high

To what extent have you had the chance to explore ideas and concepts in depth?

92%

high

To what extent does your course have the right balance of directed and independent study?

80%

med

How well have assessments allowed you to demonstrate what you have learned?

86%

med

How fair has the marking and assessment been on your course?

91%

med

How often does feedback help you to improve your work?

64%

med

How often have you received assessment feedback on time?

63%

low

How clear were the marking criteria used to assess your work?

60%

low

How easy was it to contact teaching staff when you needed to?

95%

high

How well have teaching staff supported your learning?

93%

high

How well were any changes to teaching on your course communicated?

82%

med

How well organised is your course?

85%

high

How well have the IT resources and facilities supported your learning?

91%

high

How well have the library resources (e.g., books, online services and learning spaces) supported your learning?

87%

med

How easy is it to access subject specific resources (e.g., equipment, facilities, software) when you need them?

95%

high

How clear is it that students' feedback on the course is acted on?

66%

med

To what extent do you get the right opportunities to give feedback on your course?

91%

high

To what extent are students' opinions about the course valued by staff?

85%

high

How well does the students' union (association or guild) represent students' academic interests?

77%

med

During your studies, how free did you feel to express your ideas, opinions, and beliefs?

94%

high

How well communicated was information about your university/college's mental wellbeing support services?

92%

high

Student information

See who's studying at Imperial College London. These students are taking Computing (Artificial Intelligence and Machine Learning) or another course from the same subject area.

Computing
Mode of study
Full-time100%
Gender ratio
Female16%Male84%
Where students come from
International42%UK58%
Student performance
2:1 or above91%
Number of students845
Most popular A-levels studied
SubjectGrade
Further MathematicsA*
MathematicsA*
PhysicsA*
Computer ScienceA*
ChemistryA*
Source: HESA

Graduate prospects

What graduates do next

We have no information about graduates who took Computing (Artificial Intelligence and Machine Learning) at Imperial College London.

Earnings after graduation

Earnings from Imperial College London graduates who took Computing (Artificial Intelligence and Machine Learning) - or another course in the same subject area.

Computing

Earnings

£69.7k

First year after graduation

£78.8k

Third year after graduation

£79.6k

Fifth year after graduation

Shown here are the median earnings of graduates at one, three and five years after they completed a course related to Computing (Artificial Intelligence and Machine Learning).

Source: LEO

Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree

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