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Postgraduate

MSc Data Science and AI

Lucie Brosson working on her laptop, 2021, UAL Creative Computing Institute, Photograph: Alys Tomlinson
College
UAL Creative Computing Institute
Start date
October 2024
Course length
12 months

Explore advanced applications of machine learning to create the next generation of AI products and service.

Applying for more than 1 course

You can apply for more than 1 postgraduate course at UAL but we recommend that you apply for no more than 3. Find out more in the Apply Now section.

Why choose this course at UAL Creative Computing Institute

  • Advanced machine learning: Learn advanced coding skills to develop machine learning approaches for AI products and services.
  • Data, people and society: Explore how data science approaches are key to enabling technologies that mitigate harm rather than perpetuate it.
  • Data and entrepreneurship: Examine how data science can be used in businesses to increase economic opportunity
  • The PG community: Join a creative community of students, academics and researchers who are passionate about the future of data science and AI. You will also become a member of our integrated online community for peer learning and technical support.
  • Campus location and facilities: All your classes will be taught at our High Holborn site in central London. You will also have access to workshops and facilities at all other CCI buildings in South London including Peckham Road, Greencoat and The Hub at Eagle Wharf.

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Course overview

Studying Data Science and AI at master’s level with us gives you the opportunity to deepen your core competencies in data science and AI, and to strengthen your skills in developing data- and AI-driven products and services. Furthermore, the ethical and social dimensions of data science and AI are actively explored in this course—ensuring you have a deep and critical understanding of the impacts of related technologies, and a familiarity with human-centred methods for designing and reasoning about new systems.

In this course, you will apply scientific and mathematical principles to guide the creation and evaluation of mathematical models of real-world problems, using computer programming. You will also use programming to implement, experiment with, and deploy machine learning systems. You will focus on applications of data science and AI to a broad range of domains, involving diverse types of data and content, from numerical data to text and media. You will critically engage with contemporary thinkers from diverse disciplines concerned with the ethical and social implications of data science and AI. You will also work in collaborative, creative problem solving which leverages and strengthens your technical and teamwork skills, your critical thinking, and your knowledge of application domains and stakeholders.

You will undertake a thesis project that targets your preferred technology sector or domain of work, supporting your progression to industry or further academic research.

What to expect

  • Technical skills for data science and AI: You will learn advanced coding, data science and AI skills that make use of key modern programming languages and technical frameworks, which can be applied in a wide range of data science and AI industries and beyond.
  • Project-based learning: You will complete a range of data science and AI projects, applying your skills and knowledge to real-world problems. Frequent and regular hands-on learning activities give you ample time to practice new skills while receiving rich feedback.
  • Ethical data and AI practices: You will learn how data and AI practices have the potential to impact individuals and society, and you will learn about techniques for human-centred design and critique of data and AI systems.
  • Collaboration and creativity: You will collaborate with your postgraduate peers to creatively solve problems together, bringing your varied undergraduate, professional, and personal experiences to advanced problems. These abilities and attributes are sought after by many graduate employers.
  • The CCI community: you will join a significant community of students, academics and researchers who are passionate about the future of computing. We believe that becoming an effective and ethical professional computing practitioner requires training not only in technical skills, but also in creative thinking, awareness of how computing intersects with society and the environment, and development and design practices that put people first. You will learn alongside MSc students on our other postgraduate courses. You will also be part of our integrated online community where you can access technical support, events, employment opportunities and more.
  • A supportive environment: you will have access to both technical and pastoral support and be part of a community committed to promoting accessibility, diversity and inclusion. 

Industry experience and opportunities

You will learn using industry standard tools and advanced frameworks ensuring you are ready to progress to a wide range of roles in data science and AI, across the technology sector and beyond. You will benefit from a wide range of cross-institute talks and will meet industry representatives throughout your studies.

Entrepreneurship is encouraged and the opportunity to start enterprises will be supported with business training and access to incubator programs, as well as through team entrepreneurship pedagogies.

Course units

Term 1

Advanced Algorithms and Complexity (20 credits)

You will be introduced to advanced algorithms through mathematics and programming, including linear algebra for advanced analysis of data and machine learning optimisation. You will create and analyse computational models using approaches such as stochastic and gradient algorithms, dynamic programming algorithms and primal and dual methods. This will develop your understanding of how algorithms might be improved to tackle current and emerging problems.

Advanced Mathematics and Statistics for Data Science and AI (20 credits)

You will learn advanced data structures and representations, including complex multidimensional feature processing and storage. You will be asked to demonstrate your advanced knowledge and skills in a range of mathematical and statistical approaches required for carrying out modern data science and AI. This includes calculus, discrete structures, probability theory and elementary statistics. You will also approach advanced topics in statistics including complex correlations, significance, differences in nominal and ordinal data analysis, and linear algebra.

Term 2

Critical Data Representation and Analysis (20 credits)

This unit will cover advanced professional practice principles, ethics, data protection legislation, compliance procedures and impact analysis. Through a series of case studies, you will be introduced to different critical approaches, such as social data science. You will explore in detail how representation and data abstraction at macro scale can impact individuals and marginalised groups. You will also explicitly look at the use of data in public policy making.

Artificial Intelligence and Machine Learning (20 credits)

This unit focuses on a range of contemporary AI and machine learning techniques and approaches such as RNN and LSTMs, GANs and VAEs. You will also cover reinforcement learning for natural language processing, personalisation, recommendation and audience analysis. As part of this unit, you will learn how to prepare datasets and create, test and validate your own models to solve real-world problems.

Term 3

Data, People and Society: Advanced Topics (20 credits)

In this unit, you will continue to develop your understanding of computing ethics, social data science and international data policy. You will learn how to analyse and apply critical approaches to technology development within your own work. You will be expected to apply this knowledge in your thesis project, exploring how you have embedded computing ethics and techniques in your own approach to work.

Computational Entrepreneurship (20 credits)

This MSc course has a strong focus on ‘tech for good’ and seeks to contribute to UAL’s social purpose mission. In this unit, you will develop your skills in entrepreneurship and futures thinking and learn how to embed ethical computing into your own practice. You will be introduced to a range of product development case studies, evaluating their social, cultural and ethical impact. This contextual knowledge will help you to develop realistic, informed project plans, considering team requirements, investment requirements and market placement.

Summer period

Thesis Project (60 credits)

Your final thesis project will allow you to develop a significant piece of work demonstrating the level of your knowledge and skills in relation to those delivered throughout the course. Academic staff will support you throughout your project, sharing their professional experience in contemporary data science and AI. You will also be offered the opportunity to work with staff to develop research projects based on staff expertise and topic specialisms as an option.

Learning and teaching methods

  • Lectures and seminars
  • Studio/lab-based practice and masterclasses
  • Project work
  • Technical tuition
  • Experiential team learning
  • Practical design briefs and projects
  • Collaborative problem-solving and group work
  • Panel discussions in a debate environment
  • Independent study

Watch the online open day

Fees and funding

Home fee

£13,330

This fee is correct for 2024/25 entry and is subject to change for 2025/26 entry.

Tuition fees may increase in future years for new and continuing students on courses lasting more than one year. For this course, you can pay tuition fees in instalments.

Students from countries outside of the UK will generally be charged international fees. The rules are complex so read more about tuition fees and determining your fee status.

International fee

£28,570

This fee is correct for 2024/25 entry and is subject to change for 2025/26 entry.

Tuition fees may increase in future years for new and continuing students on courses lasting more than one year. For this course, you can pay tuition fees in instalments.

Students from countries outside of the UK will generally be charged international fees. The rules are complex so read more about tuition fees and determining your fee status.

Scholarship search

Entry requirements

The standard minimum entry requirements for this course are: 

  • An honours degree in a relevant subject such as Computer Science, Data Science, Computing, Mechanical or Electrical Engineering, Joint Computer Science + Arts/Humanities programme.  

  • OR a professional qualification recognised as equivalent to an Honours degree in a technology-related or engineering discipline. 

  • AND typically, at least Grade B/Grade 6 at GCSE Mathematics.  
     

English language requirements  

  • IELTS 6.5 (or equivalent) with a minimum of 5.5 in reading, writing, listening and speaking. 

All classes are taught in English. If English isn’t your first language, you will need to show evidence of your English language ability when you enrol. For further guidance, please check our English language requirements. 

APEL - Accreditation of Prior (Experiential) Learning  

Applicants who do not meet these course entry requirements may still be considered in exceptional cases. The course team will consider each application that demonstrates additional strengths and alternative evidence. This might, for example, be demonstrated by: 

  • Related academic or work experience. 

  • The quality of the personal statement. 

  • A combination of these factors. 

Each application will be considered on its own merit, but we cannot guarantee an offer in each case. 

Selection criteria

Offers will be made based on the following selection criteria:

  • An ability to code (essential).
  • Sufficient prior knowledge and experience in a specialist subject area (e.g., computer science, creative computing, informatics, data science, AI, mathematics, statistics) or other evidence of potential to be able to successfully complete the course (essential).
  • An academic or professional background in data science, AI, computer science or a related subject area (e.g., informatics, mathematics, statistics, creative computing, etc.).
  • Willingness to work both independently and as part of a team.
  • A strong case for how the course could be applied to your ambitions, especially if your current knowledge and experience is in a different subject area.

Apply now

Application deadline

Deadline

Round 1:

13 December 2023 at 1pm (UK time)

Round 2:

3 April 2024 at 1pm (UK time)

Decision outcome

Round 1:

End of March 2024

Round 2:

End of June 2024

Round 1
Round 2
Deadline
13 December 2023 at 1pm (UK time)
3 April 2024 at 1pm (UK time)
Decision outcome
End of March 2024
End of June 2024

All applications received by 3 April will be treated equally. If there are places available after this date, the course will remain open to applications until places have been filled.

Read more about deadlines

Apply now

Application deadline

Deadline

Round 1:

13 December 2023 at 1pm (UK time)

Round 2:

3 April 2024 at 1pm (UK time)

Decision outcome

Round 1:

End of March 2024

Round 2:

End of June 2024

Round 1
Round 2
Deadline
13 December 2023 at 1pm (UK time)
3 April 2024 at 1pm (UK time)
Decision outcome
End of March 2024
End of June 2024

All applications received by 3 April will be treated equally. If there are places available after this date, the course will remain open to applications until places have been filled.

Read more about deadlines

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How to apply

Follow this step-by-step guide to apply for this course

Step 1: Initial application

You will need to submit an initial application including your personal statement and CV.

Personal statement advice

Your personal statement should be maximum 500 words and include:

  • your reasons for choosing the course
  • your current creative practice and how this course will help you achieve your future plans
  • any relevant education and experience, especially if you do not have any formal academic qualifications.

Visit our personal statement page for more advice.

CV advice

Please provide a CV detailing your education, qualifications and any relevant work or voluntary experience. If you have any web projects or other media that you would like to share, please include links in your CV. If English is not your first language, please also include your most recent English language test score.

You also need to know

Communicating with you

Once you have submitted your initial application, we will email you with your login details for our Applicant portal.

Requests for supplementary documents like qualifications and English language tests will be made through the applicant portal. You can also use it to ask questions regarding your application. Visit our After you apply page for more information.

Applying to more than 1 course

You can apply for more than 1 postgraduate course at UAL but we recommend that you apply for no more than 3 courses. You need to tailor your application, supporting documents and portfolio to each course, so applying for many different courses could risk the overall quality of your application. If you receive offers for multiple courses, you'll only be able to accept 1 offer. UAL doesn't accept repeat applications to the same course in the same academic year.

Visas and immigration history check

All non-UK nationals must complete an immigration history check. Your application may be considered by our course teams before this check takes place. This means that we may request your portfolio and/or video task before we identify any issues arising from your immigration history check. Sometimes your history may mean that we are not able to continue considering your application. Visit our Immigration and visas advice page for more information.

External student transfer policy

UAL accepts transfers from other institutions on a case-by-case basis. Read our Student transfer policy for more information.

Alternative offers

If your application is really strong, but we believe your strengths and skillset are better suited to a different course, we may make you an alternative offer. This means you will be offered a place on a different course or at a different UAL College.

Deferring your place

We do not accept any deferral requests for our postgraduate courses. This means that you must apply in the year that you plan to start your course and you will not be able to defer your place to start at a later date.

Application deadlines

For postgraduate courses at UAL there are 2 equal consideration deadlines to ensure fairness for all our applicants. If you apply ahead of either of these deadlines, your application will be considered on an equal basis with all other applications in that round. If there are places available after the second deadline, the course will remain open to applications until places have been filled.

Careers

Computing graduates are highly sought after across sectors and our degrees facilitate progression to a wide range of careers in both industry and academia. Graduates can join large companies or start their own business using their engineering skills and their knowledge of computational innovation.

Graduates can become:

  • Data scientists for large and small technology companies
  • Specialists in NLP, voice technology and computer vision
  • Data science researchers
  • IT professionals across a variety of sectors
  • Founders of technology start-ups in sectors such as finance, healthcare and the creative industries.

Opportunities for Further study:

  • PhD level study both within the CCI and at other institutions nationally and internationally