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Data Science and Artificial Intelligence

MSc

Start dates: September 2025 / September 2026

Full time: 12 months

Part time: 24 months

Location: Headington

School(s): School of Engineering, Computing and Mathematics

Overview
Course details
Careers
Entry requirements
How to apply
Tuition fees

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Overview

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.
 

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Why Oxford Brookes University?

  • Use of real case scenarios
    Many assignments will be based on big data sets based on real case scenario to solve real world problems. You will also have the opportunity to use data from your workplace. 
  • Combine the pillar of data science
    You will use Mathematics, Programming and AI techniques to gather, model, transform, process and analyse data.

     
  • Extra curriculum: Autonomous vehicles
    The autonomous vehicle team from OBR requires students with skills in data analysis and AI to work on  software for the car, giving you valuable experience.

     

Course details

Course structure

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 will open in the 2024/25 academic year. 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

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

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.

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.

Research

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:

Careers

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.
 

Entry requirements

International qualifications and equivalences

How to apply

Application process


Apply now

Tuition fees

Please see the fees note
Home (UK) full time
£9,150
Home (UK) part time
£1,020 per single module
International full time
£18,050
Home (UK) full time
£9,700
Home (UK) part time
£1,080 per single module
International full time
£18,350

Questions about fees?

Contact Student Finance on:

financefees@brookes.ac.uk

Tuition fees

2024 / 25
Home (UK) full time
£9,150
Home (UK) part time
£1,020 per single module
International full time
£18,050
2025 / 26
Home (UK) full time
£9,700
Home (UK) part time
£1,080 per single module
International full time
£18,350

Questions about fees?

Contact Student Finance on:

+44 (0)1865 534400

financefees@brookes.ac.uk

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.

Part-Time UK Faculty Scholarship Postgraduate Master's Loan - England

All financial support and scholarships

View all funding opportunities for this course

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.