MSc Data ScienceFind a programme
New programme for 2020
|Faculty||Faculty of Engineering|
|Programme length||One year full-time|
|Location of programme||Clifton campus|
|Part-time study available||No, full-time only|
|Start date||September 2020|
If you want to improve the world through the responsible use of data, the MSc in Data Science will give you the skills to do so. You will learn how to understand, in depth, the computational and statistical principles of modern data science and be skilled at the rigorous and ethical application of these techniques to real-world challenges.
Whether you have a background in numerate sciences, engineering, or computer science, the course will provide you with the skills to succeed in this exciting and fast-moving discipline and will equip you with excellent employment prospects to pursue roles in industry as either a data scientist or data engineer as well as for research and development roles.
This MSc aims to:
- Equip you with the ability to work across disciplinary boundaries in the effective application and deployment of data-intensive solutions in a variety of contexts.
- Give graduates a breadth and depth of knowledge and skills in computational, machine learning, and statistical principles and the capability for insightful large-scale data analysis, so you will be able to specify and implement analytical pipelines for real-world data at scale.
- Provide you with a good understanding of the ethical issues in the application of contemporary data science techniques to real-world challenges so you can be conversant with arguments concerning the risks and potential benefits and disadvantages arising from the deployment of these technologies.
- Enable you to independently initiate data science projects specified at a high-level perspective, leading them from scoping onward to completion, while exercising appropriate project management methods and maintaining stakeholder engagement.
The MSc in Data Science has been co-designed with industrial partners and is highly relevant to rewarding employment opportunities. There is a strong emphasis on responsible innovation and ethics to encourage you to use your knowledge and skills for societal good in the workplace or through further research. The course is closely associated with excellent research in the university, ensuring leading edge teaching.
Fees for 2020/21
We charge an annual tuition fee. Fees for 2020/21 are as follows:
- UK/EU: full-time
- Overseas: full-time
- Channel Islands/Isle of Man: full-time
Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to a five per cent increase in fees each year. Find out more about tuition fees.
University of Bristol students and graduates can benefit from a ten per cent reduction in tuition fees for postgraduate study. Check your eligibility for an alumni scholarship.
Funding for 2020/21
Further information on funding for prospective UK, EU and international postgraduate students.
You'll take either a 20-credit unit in Software Development: Programming & Algorithms, or, if you already have software development skills, a 20-credit unit in Statistical Computing will be required.
The remainder of the MSc consists of the following compulsory units:
- Large-Scale Data Engineering (20 credits)
- Technology, Innovation, Business, and Society (20 credits)
- Introduction to Artificial Intelligence (10 credits)
- Text Analytics (10 credits)
- Visual Analytics (20 credits)
The final compulsory unit, a Data Science Mini-project (20 credits), is a group activity which will be aligned, wherever possible, with an external client.
To complete your studies, a 60-credit individual research or implementation project can be chosen from a selection proposed by project supervisors. This unit will provide you with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work in the field of Data Science. The aim of this unit is to give you a substantial opportunity to integrate material from all taught units and demonstrate the breadth and depth of your learning on the MSc.
Visit our programme catalogue for full details of the structure and unit content for our MSc in Data Science
Applicants must hold/achieve a minimum of an upper-second class honours degree (or international equivalent) in numerate science, computer science, or engineering.
See international equivalent qualifications on the International Office website.
English language requirements
If English is not your first language, you need to meet this profile level:
Further information about English language requirements and profile levels.
Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.
Graduates from this MSc will be keenly sought after in roles such as lead data scientists or lead data engineers, capable of critically evaluating and synthesising research literature, developing and deploying scalable data-processing systems, and communicating with others in their field and in other disciplines. Top graduates from this degree will be able to pro-actively advance the development of data science and related technologies.
18 August for home and EU applicants
Due to very high demand, applications are now closed to students classified as overseas for fee purposes. The School continues to welcome applications from Home EU/UK applicants, that fulfil our admissions criteria, in order to select a balanced student cohort. As students from different regions tend to apply at different points in the application period, applications from some regions may close earlier in the year.
Request more information
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Enquiries team Phone: +44 (0) 117 394 1649 Email: email@example.com
School website: School of Computer Science, Electrical and Electronic Engineering, and Engineering Mathematics
Department website: Computer Science
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REF 2014 results
- 20% of research is world-leading (4 star)
- 45% of research is internationally excellent (3 star)
- 30% of research is recognised internationally (2 star)
- 5% of research is recognised nationally (1 star)
Results are from the most recent UK-wide assessment of research quality, conducted by HEFCE. More about REF 2014 results.