COMP7037
20 credits
This module is designed to equip you with the tools necessary for the scholarship and research skills needed for the computer science and cyber security fields...
MSc Data Science and Artificial Intelligence
Combine advanced data analysis with artificial intelligence to investigate complex problems and develop evidence-based approaches.
Key facts
- Duration
- Full time: 12 months
- Part time: 24 months
- Starts
- September 2027
- Level
- Master's and postgraduate
- Course code
- MSC-DAI
- Location
- Headington
- School
- School of Engineering, Computing and Mathematics
About this course
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.
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.
New State-of-the-art facilities
All Computing courses are based innew, custom designed buildings at our main Headington site. 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.
Research expertise
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:
Entry requirements
Entry requirements
| Qualification | Typical offer |
|---|---|
| IELTS | IELTS 6.0 overall with 6.0 in all skills. For more information, please see our English language 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.
Fees and funding
Fees
| Fee types | 2026/27 | 2027/28 |
|---|---|---|
| Home full-time | £9,950 | £10,250 |
| Home part-time | £4,975 | £5,125 |
| International full-time | £19,600 | £20,800 |
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.
Questions about fees?
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 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.
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.
Year 1
Compulsory modules
COMP7001
20 credits
This module introduces you to problem solving and programming in Python and teaches you core programming techniques essential for performing data science tasks.
COMP7035
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...
COMP7036
20 credits
This module will introduce you with the fundamental statistical concepts required to model and analyse data.
COMP7034
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...
COMP7029
20 credits
On this module you will focus on current practices, skills and techniques applied to managing software development related projects, individually and in project...
ARCH7030
50 credits
This is your opportunity to undertake a self-directed piece of work and explore an issue or theme in depth. You will develop your research ideas during semester...
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.
How to apply
Our courses are reviewed regularly as part of our quality assurance framework, so module availability and course structures may vary from what is listed here. On rare occasions, we may also need to make updates to our course programmes after publication; for full details, please visit our changes to programmes page (opens in a new tab)