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Artificial Intelligence
Receive intensive training in programming and the fundamentals of artificial intelligence.
Receive intensive training in artificial intelligence, machine learning, and programming
Explore the ethical and legal issues arising from new developments in AI
Work on projects with leading companies working on AI applications
Course key facts
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Qualification
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MSc
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Duration
1 year
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Start date
September 2024
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Study mode
Full-time
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Fees
£22,250 Home
£41,750 Overseas
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Delivered by
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Location
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South Kensington
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Minimum entry standard
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First class Honours in mathematics, physics, engineering or other degree with substantial mathematics content
Course overview
Aimed at mathematically-minded STEM graduates, this Master's degree delivers intensive training in programming and the fundamentals of artificial intelligence (AI).
As well as learning the technical skills required for this growing area of computing science, you'll have the chance to explore realistic applications through group and individual projects.
This course offers you the chance to forge links with major technology companies and work within industry-initiated projects.
Students with a substantial background in computing who wish to explore other areas of computing alongside specialised options in AI and machine learning may prefer to consider our MSc Computing (Artificial Intelligence and Machine Learning) degree.
Structure
This page reflects the latest version of the curriculum for this year of entry. However, this information is subject to change.
Find out more about potential course changes.
You’ll take all of these core modules.
Core modules
Gain insights into the different types of problems that exist in machine learning and the basic algorithms used to address them.
Understand the fundamentals of Python and learn how to write procedural, object-oriented and functional programs in Python.
Learn how to apply knowledge of domain properties and agent architectures in the representation of problems in symbolic AI.
Explore the issues and implications around ethics and philosphical problems, fairness and bias, and justifiable explanations in AI decision-making.
Obtain practical experience in developing AI applications and using software engineering techniques in the design and implementation of large programs.
In addition to your core modules, you will choose five optional modules in total: four or all five must be from Group 1, and either zero or one from Group 2.
This list is indicative of the choices you can expect. Your options may differ from those listed.
Group 1
Explore how images are formed, how they are represented on computers and how they can be processed by computers to extract semantic information.
Learn how to describe the core principles of autonomous systems learning and calculate mathematical solutions to problems using reinforcement learning theory.
Develop a deeper understanding of optimal decision making models, algorithms and applications to engineering, finance, and machine learning.
Learn how to design and implement modern statistical machine learning methodologies, as well as inference mechanisms.
Develop intellectual and practical skills in the use of modal logics for knowledge representation and automated reasoning in artificial intelligence.
Gain an in-depth understanding of logic-based learning, starting from its key foundation concepts and principles before moving to more recent advances.
Explore the fundamental concepts and advanced methodologies of deep learning and relate them to real-world problems.
Discover why knowledge representation and reasoning are essential components of an intelligent system and are at the core of artificial intelligence research.
Examine how probability can be used to make decisions by a computer and advance your understanding of inference networks and linear and non-linear methods in statistical pattern recognition.
Explore the fundamental concepts and advanced methodologies of machine learning for imaging and relate them to real-world problems in computer vision and medical image analysis.
Acquire the techniques and tools needed to devise and develop natural language processing (NLP) components and applications.
Engage with the emerging field of robot learning and discover how robots can acquire skills and control their bodies using machine learning techniques.
Assess the exciting field of mobile robotics, at a time when cutting-edge robots are beginning to leave the research laboratory to tackle real-world tasks.
Explore applications of artificial intelligence technologies that will improve or transform existing financial, health and other systems.
Understand the rationale behind the theoretical end of computational neuroscience and basic principles of the tools needed to simulate the brain's intelligent behaviour in this interdisciplinary module.
Gain a flavour of different aspects of the broad and ever-expanding field of graph theory and learning, including conventional graph data analysis methods and the nascent field of graph neural networks.
Explore the intersection of robotics and human-computer interaction, covering user-centric and user study design, data analysis, and relevant theoretical foundations, in this exciting new field.
Implement and operate a simplified machine learning-based system in this module covering engineering concepts underpinning trustworthy systems. Looks at all aspects of systems, including data ingestion, user experience, regulation and wider society.
Group 2
Understand the basic concepts of quantitative finance and financial engineering and build awareness of the major decision, hedging, and pricing problems in finance.
Analyse the foundational principles behind decentralised ledgers and apply them to current research in cryptocurrencies.
Discover the basic notions of quantum computing and be introduced to Quantum Bits, Quantum Entanglement and Quantum Algorithms.
Delve into the deep connections between information theory, statistics and machine learning, in this module linking computing, statistics and geometry. Includes mathematical and computational exercises, and provides crucial theoretical background for a career in data science or machine learning.
Demonstrate independence and originality on an individual project.
You'll put into practice some of the techniques that have been taught throughout the course and have the opportunity to develop a significant AI application.
Teaching and assessment
Balance of teaching and learning
Key
- Taught
- Independent study
- 12% Taught (lectures and tutorials)
- 88% Independent study
Teaching and learning methods
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Group project
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Individual project
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Seminars
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Tutorials
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Computing labs
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Virtual learning environment
Balance of assessment
Key
- Assessed coursework
- Examinations (practical and written)
- Group and individual project / internship
- 20% Assessed coursework
- 30% Examinations (practical and written)
- 50% Group and individual project / internship
Entry requirements
How to apply
Applications are now closed for 2024 entry.
There is no application fee for MRes courses, Postgraduate Certificates, Postgraduate Diplomas, or courses such as PhDs and EngDs.
If you are applying for a taught Master’s course, you will need to pay an application fee before submitting your application.
The fee applies per application and not per course.
- £80 for all taught Master's applications, excluding those to the Imperial College Business School.
- £100 for all MSc applications to the Imperial College Business School.
- £150 for all MBA applications to the Imperial College Business School.
If you are facing financial hardship and are unable to pay the application fee, we encourage you to apply for our application fee waiver.
Find out more about how to apply for a Master's course, including references and personal statements.
An ATAS certificate is not required for students applying for this course.
Tuition fees
Home fee
2024 entry
£22,250
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
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 courses starting on or after 1 August 2024, the maximum amount is £12,471. The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
Overseas fee
2024 entry
£41,750
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
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 courses starting on or after 1 August 2024, the maximum amount is £12,471. The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
How will studying at Imperial help my career?
Develop the skills needed by industries recognising AI's transformative potential.
Find employment in a variety of sectors, from healthcare to manufacturing to the automotive industry (driverless cars).
Computing graduates are sought after in roles such as application/web development, networking, AI, media, finance, robotics, and computer games.
Other potential career paths include chip design, cyber security, data management, bio-medical systems and transport.
Further links
Contact the department
- Telephone: +44 (0) 20 7594 8298
- Email: doc-mscadmissions@imperial.ac.uk
Course Director: Dr Anandha Gopalan
Visit the Department of Computing website.
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There are some important pieces of information you should be aware of when applying to Imperial. These include key information about your tuition fees, funding, visas, accommodation and more.
You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.
Programme specifications