Program Overview

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Data Science and Artificial Intelligence

MSc

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.

Why Oxford Brookes University?

• Use of real case scenarios
• Combine the pillar of data science
• Extra curriculum: Autonomous vehicles

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.

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

Compulsory modules

• Research Methods (20 credits)
• Programming and Software Tools (20 credits)
• Principles of Data Science (20 credits)
• Statistical Modelling (20 credits)
• Machine Learning and Data Mining (20 credits)
• Group Software Project (20 credits)

Final project

• Dissertation (60 credits)

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:

• Centre for AI, Culture and Society (CAICS)
• Advanced Reliable Computer Systems (ARCoS)
• Applied Software Engineering and Data Analytics (ASEDA)
• Cloud Computing and Cybersecurity group (CCC)
• Machine Learning and Robotics Group (MLR)
• Visual Artificial Intelligence Laboratory (VAIL)

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

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.

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.

Tuition fees

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)

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

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.

Optional costs

• Travel and associated costs if relevant when undertaking work placements: £30-700 per year
• If you are considering bringing your own computer, most of the software we use is on Windows machines though there is some use of Linux. We do not use Apple MacOS and their use is not required but some students do choose to bring MacOS machines so a Mac can be a viable choice if you so wish: £
• It’s your responsibility to cover print / binding costs where coursework submission is required. Please note that a lot of the coursework is now submitted online: From £30
• You may choose to purchase books to support your studies. Many books on our reading lists are available via the Library, or can be purchased secondhand: £20-60 per book
• Accommodation fees in Brookes Letting (most do not include bills): £94-265 per week
• Accommodation fees in university halls (bills included, excluding laundry costs): £122-180 per week
• Graduation costs include tickets, gowning and photography. Gowns are not compulsory but typically students do hire robes, starting at £41: Typically £0-200
• Students are responsible for their own travel to and from university for classes. For the 2025/26 academic year, the University is introducing an alternative subsidised travel offer for all students with further information on our Travel webpages: From £10