Data Science and Artificial Intelligence


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Key facts

Start dates

September 2024 / September 2025



Course length

Full time: 12 months

Part time: 24 months


The MSc in Data Science and Artificial Intelligence provides you with the skills and understanding necessary to gather, identify, process, analyse and use data using AI techniques. You will learn fundamental theory and practise concepts that will equip you with the professional skills needed in the workplace.

The explosion and wealth of available data in a wide range of application domains gives rise to new challenges and opportunities in all areas. One challenge is how to use this unprecedented scale of data, and how to gain further insights and knowledge to improve the quality of offered products and services. Artificial Intelligence plays a central role in understanding data and developing intelligent systems that can learn from themselves and assist organisations in strategic decision making.

Male student at computer

How to apply

Entry requirements

Specific entry requirements

To join this course you'll need a 2:2 bachelor's degree in the physical or social sciences where you have developed analytical knowledge and understanding in mathematical sciences.

Typically this includes applicants with knowledge and familiarity with basic computing, mathematics and statistics concepts and methods at bachelor's degree level.

Applicants with other qualifications, plus work experience from other fields, who have quantitative skills and familiarity with data analysis and modelling ideas will also be considered. 

Please also see the University's general entry requirements.

English language requirements

If your first language is not English you will require a minimum IELTS score of 6.0 overall with 6.0 in all components.

Please also see the University's standard English language requirements.

International qualifications and equivalences


English requirements for visas

If you need a student visa to enter the UK you will need to meet the UK Visas and Immigration minimum language requirements as well as the University's requirements. Find out more about English language requirements.

Pathways courses for international and EU students

We offer a range of courses to help you meet the entry requirements for your postgraduate course and also familiarise you with university life in the UK.

Take a Pre-Master's course to develop your subject knowledge, study skills and academic language level in preparation for your master's course.

If you need to improve your English language, we offer pre-sessional English language courses to help you meet the English language requirements of your chosen master’s course.

Terms and Conditions of Enrolment

When you accept our offer, you agree to the Terms and Conditions of Enrolment. You should therefore read those conditions before accepting the offer.

Application process

Tuition fees

Please see the fees note
Home (UK) full time
£1,130 per single module

Home (UK) part time
£1,130 per single module

International full time

Home (UK) full time

Home (UK) part time
£1,020 per single module

International full time

Questions about fees?

Contact Student Finance on:

Tuition fees

2023 / 24
Home (UK) full time
£1,130 per single module

Home (UK) part time
£1,130 per single module

International full time

2024 / 25
Home (UK) full time

Home (UK) part time
£1,020 per single module

International full time

Questions about fees?

Contact Student Finance on:

+44 (0)1865 534400

Fees quoted are for the first year only. If you are studying a course that lasts longer than one year, your fees will increase each year.

The following factors will be taken into account by the University when it is setting the annual fees: inflationary measures such as the retail price indices, projected increases in University costs, changes in the level of funding received from Government sources, admissions statistics and access considerations including the availability of student support.

How and when to pay

Tuition fee instalments for the semester are due by the Monday of week 1 of each semester. Students are not liable for full fees for that semester if they leave before week 4. If the leaving date is after week 4, full fees for the semester are payable.

  • For information on payment methods please see our Make a Payment page.
  • For information about refunds please visit our Refund policy page

Additional costs

Please be aware that some courses will involve some additional costs that are not covered by your fees. Specific additional costs for this course are detailed below.

Funding your studies

Financial support and scholarships

Featured funding opportunities available for this course.

All financial support and scholarships

View all funding opportunities for this course

Learning and assessment

The MSc in Data Science and Artificial Intelligence has a modular course-unit design. This provides you with flexibility and choice if you are considering taking the course part time

To qualify for a master’s award  you must pass all the modules listed in the “Study modules” section below. For the PGDip and PGCert you will be able to select modules from that list. Please contact us for more details. 

Brand new facilities

All Computing courses are moving from Wheatley Campus to brand new, custom designed buildings at our main Headington site. These buildings are expected to open in September 2024, but as with any large-scale building project those timescales could change. You'll benefit from state-of-the-art facilities and equipment including a VR cave, digital, computing and robotics labs, as well as social learning spaces, teaching rooms and cafe space.

Male and female students taking notes on laptops

Study modules

Taught modules

Compulsory modules

  • Research Methods (20 credits)

    This module will equip you with the skills necessary to perform research and employ effective study methods which will underpin your dissertation.

  • Programming and Software Tools (20 credits)

    This module introduces you to programming in Python and teaches you core programming techniques essential for performing data manipulation, data processing and data analyses

  • Principles of Data Science (20 credits)

    This module presents an overview of core data science concepts and tools, focusing on real-life data science research questions. This module will teach you to analyse and visualise large data sets by using well known programming libraries and tools.

  • Statistical Modelling (20 credits)

    This module will introduce you with the fundamental statistical concepts required to model and analyse data.

  • Machine Learning and Data Mining (20 credits)

    The module aims to provide you  an introduction to the key concepts in data mining and machine learning. It covers the fundamentals of machine learning methodologies and data mining, information extraction and pattern recognition techniques. The module will enable you to analyse problems, critically evaluate different approaches that are available and create an effective solution.

  • Group Software Project (20 credits)

    This module teaches you the current practices, skills and techniques applied to managing software development in a team related. The module uses live projects in data science  to underpin the learning and considers requirements engineering, project management, risk, quality assurance, usability and HCI issues. 

Final project

Compulsory modules

  • Dissertation (60 credits)

    For the MSc you're required to complete a compulsory dissertation on a data science focussed topic related to your programme of study.

    The exact content of each dissertation will vary in accordance to the title but will involve you completing a literature review and research of the topic at an advanced level, the preparation of a project proposal, the application of analytical techniques and academic approaches to the generation of alternative solutions and synthesis of a solution for the complex problem in hand, together with the presentation of the solution in oral and written form. 

Please note: As our courses are reviewed regularly as part of our quality assurance framework, the modules you can choose from may vary from those shown here. The structure of the course may also mean some modules are not available to you.

Learning and teaching

In the MSc, you’ll complete 6 taught modules of 20 credits each, and a dissertation of 60 credits.

We’ll help you understand everything you’ll need for your career, including; how to analyse and process data, how to recommend products based on this data,  and predicting future trends in the market.

You’ll complete your dissertation over the summer, with support from a supervisor. This is your opportunity to put your new knowledge to work on a project of your choice.

Our course has a supportive teaching and learning strategy based on active student engagement. We use a variety of teaching and assessment methods such as critical appraisal reports, data analysis reports, software applications, and presentations

Learning methods include:

  • blended learning
  • formal lectures
  • problem solving practicals
  • guided independent learning
  • use of the computer based learning environment ‘Moodle’
  • independent research
  • software data analyses
  • experiments.


Assessment methods used on this course

Assessment  is 100% coursework and covers a range of activities including:

  • reports
  • data analysis
  • programming
  • presentations.

We encourage you to relate the assessment tasks with professional activities. And to relate your achievements with professional standards. 

You will have the opportunity to work independently and in groups. Where appropriate, we use self and peer assessment to encourage you to get involved in your own professional development.


The School of Engineering, Computing and Mathematics is home to world-leading and award-winning research.

Our focus is on user-inspired original research with real-world applications. We have a wide range of activities from model-driven system design and empirical software engineering through to web technologies, cloud computing and big data, digital forensics and computer vision.

Staff and students collaborate on projects supported by the EPSRC, the EU, the DTI, and several major UK companies.

Computing achieved an excellent assessment of its UoA (Unit of Assessment) 11 return for REF 2014 (Research Excellence Framework).

Students on this course can be involved with research in the following research groups:

After you graduate

Career prospects

Jobs around data science and AI (data scientist, data analytics, data engineer, data manager)  have become increasingly important over the last decade. This is because data science holds the key to tackling the fundamental problem created by the revolution in the development of computers and automated systems in the 20th Century: how to make sense of the unprecedented volumes of data that are generated daily? 

Currently, global demand for combined statistical and computing expertise outstrips supply, with evidence-based predictions suggesting a major shortage in this area for at least the next 10 years. For graduates in data science and AI this shortage presents opportunities to enhance career progression in one of the most crucial areas of modern science.

Graduates from the programme will be ideally equipped for a career in a wide variety of industries. Graduates are employed across a whole range of jobs including Data Scientists, Data Analyst, Statisticians and Data Engineers.

Programme changes:
On rare occasions we may need to make changes to our course programmes after they have been published on the website. For more information, please visit our changes to programmes page.