AI and Data Science MSc

This course is in clearing with spaces available


Course options

Select year


  • MSc AI and Data Science, home applicant, full time

    • Home Applicant
    • Full time, 1/2 years
    • Pound 10800 Per year
  • MSc AI and Data Science, home applicant, part time

    • Home Applicant
    • Part time
    • Pound 1800 Per 30 credit module
  • MSc AI and Data Science, international applicant, full time

    • International Applicant
    • Full time, 1/2 years
    • Pound 15960 Per year

MSc with Placement Year

  • MSc AI and Data Science, home applicant, full time

    • Home Applicant
    • Full time, 1/2 years
    • Pound 10800 Per year
  • MSc AI and Data Science, home applicant, part time

    • Home Applicant
    • Part time
    • Pound 1800 Per 30 credit module
  • MSc AI and Data Science, international applicant, full time

    • International Applicant
    • Full time, 1/2 years
    • Pound 15960 Per year

Course modules

Select year

Software Engineering

Artificial Intelligence & Machine Vision

Machine Learning on Big Data

Mental Wealth; Professional Life (Dissertation)

The Fundamentals of Artificial Intelligence

Industrial Placement

NOTE: Modules are subject to change. For those studying part time courses the modules may vary.

Your future career

Your future career

With your qualification you’ll be equipped to launch or enhance a career in the artificial intelligence and/or data science sectors, as well as giving them the skills they need to work in related consultancy or to start a new tech business. Career opportunities include (but are not limited to):

  • Applied Artificial Intelligence and Data Science professional
  • Graduate analyst
  • Business analyst
  • Business Intelligence Developer
  • (Big) Data engineer/analyst/scientist/architect
  • Machine learning developer
  • Software engineer/architect
  • Data mining expert
  • Technology consultant
  • Digital marketing analyst or manager

You may even want to start a new tech business. Explore the different career options you can pursue with this degree and see the median salaries of the sector on our Career Coach portal.

How we support your career ambitions

We offer dedicated careers support, further opportunities to thrive, such as volunteering and industry networking. our courses are created in collaboration with employers and industry to ensure they accurately reflect the real-life practices of your future career and provide you with the essential skills needed. You can focus on building interpersonal skills through group work and benefit from our investment in the latest cutting edge technologies and facilities.

Career Zone

Our dedicated and award-winning team provide you with careers and employability resources, including:

  • Online jobs board for internships, placements, graduate opportunities, flexible part-time work.
  • Mentoring programmes for insight with industry experts 
  • 1-2-1 career coaching services 
  • Careers workshops and employer events 
  • Learning pathways to gain new skills and industry insight

Mental Wealth programme

Our Professional Fitness and Mental Wealth programme which issues you with a Careers Passport to track the skills you’ve mastered. Some of these are externally validated by corporations like Amazon and Microsoft.

See more details

We are careers first

Our teaching methods and geographical location put us right up top

  • Enterprise and entrepreneurship support 
  • We are ranked 6th for graduate start-ups 
  • Networking and visits to leading organisations 
  • Support in starting a new business, freelancing and self-employment 
  • London on our doorstep

What you'll learn

Knowledge and Understanding

  • Consistently produce correct and well-structured programs using state-of-the-art methodologies and software engineering design.
  • Importance of current and emerging methodologies and best practices for AI and data science through a critical understanding of the subject literature and research.
  • The foundations of mathematics, probabilities, AI, data mining, and data science methods including the principles and concepts of a range of artificial paradigms.
  • Demonstrate a broad variety of fundamental and advanced topics relating to AI and data science to solve real-life problems.
  • Professional, legal, social, cultural, and ethical issues related to AI and data science.

Thinking (Intellectual) skills

  • The ability to identify, analyse and formulate criteria and specifications appropriate to a given AI and data science problem.
  • The ability to model problems and their solutions with an awareness of any trade-offs involved.
  • The ability to evaluate systems, processes, or methodologies in terms of in-place performance measurement and possible trade-offs.
  • The ability to deal with complex issues systematically and creatively.
  • The ability to plan and execute a substantial research or development-based project and to report the work in the form of a dissertation.

Subject-based Practical skills

  • Identify the appropriate tools, software libraries and algorithms to develop AI and data science applications.
  • Design and create intelligent and practical solutions to real-world problems by applying industry-standard principles across a range of platforms and technologies relevant to AI and data science subjects.
  • Critically assess the design and implementation of AI and data science programs and propose ways to reuse or improve them.
  • Communicate with technical and non-technical audiences and use the developed data applications using AI and data science disciplines and methodologies.

Skills for life and work (general transferable skills)

  • The ability to make effective use of general IT facilities and resources.
  • The ability to plan, work and study independently and as a member of a team and to review and use the literature, current developments and processes reflecting critically on successes and failures.
  • Time management and organisational skills, including the ability to manage your own learning and development
  • Understand the importance of embedding professional, legal, social, cultural, and ethical considerations into the development of applications.
  • The ability to present ideas, arguments, and results in the form of a well-structured written report.

How you'll learn

The course is taught through a series of face-to-face lectures, workshops, and lab-based learning as a way of securing a knowledge base. It uses holistic, experiential, and self-directed learning approaches as the basis for adult learning, as well as a problem-based learning approach as a way of addressing the complexity of situations in the real world.

Guided independent study

When not attending timetabled lectures, you will be expected to continue learning independently through self-study. This will involve reading articles and books, watching videos, undertaking research, working on individual and group projects as well as preparation of essays, reports and presentations and production of major self-directed projects. Your independent learning is supported by a range of fantastic, industry-standard facilities.  You’ll also have access to online resources, the library and Moodle.

Academic support

Our academic support team values course members as active learners with differing and valuable experiences. They provide the supervision needed to develop reflexive and reflective software engineering experts in professional settings. We also have a Student Hub which is the central point for students to access all services including academic support, and disability support, to mention a few.

Dedicated personal tutor

Our dedicated and specialist staff will support you throughout the course and you’ll be assigned to a personal tutor when you arrive to oversee. This is the member of staff, who will provide academic guidance, be a support throughout your time at UEL and who will show you how to make the best use of all the help and resources that we offer.


You will spend around 600 hours of timetabled learning and teaching activities during the year. This includes practical sessions, seminars, and reflection of work-based practice to enforce learning and professional skills.

The approximate percentages for this course are:

  • Year 1 -  scheduled teaching:: 48 hours. Workshops/practical: 72 hours. Guided independent study: 480 hours, per semester.
  • Year 2 (optional): 300 hours industrial placement

How you will be assessed


Knowledge is assessed by:

  • Tutorials (in class and at the end of the year)
  •  Individual/group projects, coursework and reports
  • Group assessments
  • Presentations
  • Dissertation


Thinking skills are assessed by:

  • Coursework
  • All assessment tasks set (especially related to critical thinking)
  • Use of appropriate problem-solving skills
  • Project work

Practical skills are assessed by:

  • Assessment tasks requiring the use of general and specialised IT applications
  • Demonstration of projects/tasks
  • Use of tools in designing algorithms
  • Practical reports

Skills for life and work (general skills) are assessed by:

  • Evidence of group and team working
  • Ability to work under time constraints
  • Project work
  • Group work 

The approximate percentages for this course are:

  • Year 1: 75 per cent coursework, 25 per cent exams

You’ll always receive detailed feedback outlining your strengths and how you can improve. We aim to provide feedback on assessments within 10 working days. 

Campus and facilities

Docklands Campus, London, E16 2RD