(Full time) 2021 start
Data Science and Analytics MSc
Coronavirus information for applicants and offer holders
We hope that by the time you’re ready to start your studies with us the situation with COVID-19 will have eased. However, please be aware, we will continue to review our courses and other elements of the student experience in response to COVID-19 and we may need to adapt our provision to ensure students remain safe. For the most up-to-date information on COVID-19, regularly visit our website, which we will continue to update as the situation changes www.leeds.ac.uk/covid19faqs
Overview
We are surrounded by data. The variety and amount we collect and store grows every day, from the simplest of retail transactions to the complex and intimate medical records of millions.
Why do we store data? Where do we store it? How do we retrieve it? What do we use it for?
There is an increasing demand for people who can manage and control the way data is used. These individuals require an understanding of computer science and mathematics, as well as a familiarity with the data needs and processes of a number of different areas, including healthcare, business, government and the environment.
The Data Science and Analytics Masters degree offers you the opportunity to develop a range of relevant skills including:
- analysing structured and unstructured data
- analysing large datasets
- critically evaluating results in context
- getting insights from data
The course combines expertise from the Schools of Computing, Geography and Mathematics with that of Leeds University Business School.
This collaboration allows you to benefit from a range of data science perspectives and applications, allowing you to tailor the course to match your own career ambitions.
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Course content
The course will equip you with the knowledge and skills you need to meet the challenges of data science in the modern world.
Modules can be chosen from the School of Mathematics; the School of Computing; the School of Geography and Leeds University Business School.
Mathematics modules are available for students who are not from a mathematics/statistics background, while Computing modules will be suitable for students on this programme who are not from a computer science background.
The course will introduce you to different perspectives on data science, including the mathematical and computational underpinnings of the subject and its applications in specific contexts.
Your dissertation will enable you to span academic disciplines with supervision from both areas. For this project you will interpret a real-world problem, covering data elucidation, analysis, and application, building the key skills you will use in a professional or academic career.
Want to find out more about your modules?
Take a look at the Data Science and Analytics module descriptions for more detail on what you will study.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
Modules
Year 1
Compulsory modules
- Data Science 15 credits
- Learning Skills through Case Studies 15 credits
- Dissertation in Data Science and Analytics 60 credits
Optional modules (selection of typical options shown below)
- Information Visualization 10 credits
- Bio-Inspired Computing 15 credits
- Machine Learning 15 credits
- Artificial Intelligence 15 credits
- Algorithms 15 credits
- Data Mining and Text Analytics 15 credits
- Semantic Technologies and Applications 15 credits
- Scheduling 15 credits
- Graph Theory: Structure and Algorithms 15 credits
- Geographic Data Visualisation & Analysis 15 credits
- Geodemographics and Neighbourhood Analysis 15 credits
- Big Data and Consumer Analytics 15 credits
- Predictive Analytics 15 credits
- Applied GIS and Retail Modelling 15 credits
- Effective Decision Making 15 credits
- Advanced Management Decision Making 15 credits
- Business Analytics and Decision Science 15 credits
- Forecasting and Advanced Business Analytics 15 credits
- Linear Regression and Robustness 15 credits
- Statistical Theory 15 credits
- Stochastic Calculus for Finance 15 credits
- Multivariate Analysis 10 credits
- Time Series 10 credits
- Bayesian Statistics 10 credits
- Generalised Linear Models 10 credits
- Statistical Theory and Methods 15 credits
- Statistical Learning 15 credits
- Multivariate Methods 15 credits
- Multivariate and Cluster Analysis 15 credits
- Time Series and Spectral Analysis 15 credits
- Bayesian Statistics and Causality 15 credits
- Generalised Linear and Additive Models 15 credits
- Statistical Computing 15 credits
- Transport Data Science 15 credits
Learning and teaching
Teaching is by lectures, tutorials, seminars and supervised research projects.
On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.
Assessment
Assessment is by a range of methods, including formal examination, assignments, coursework, reports and practical activities.
Applying, fees and funding
Entry requirements
A bachelor degree with a 2:1 (hons) in a subject containing a substantial mathematical and statistical component.
Successful applicants will have strong grades in relevant mathematical modules. We may ask for further detailed module information if these are not clear on your transcript. We do not normally accept degrees in Accountancy or Finance.
We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks).
If you need to study for longer than 10 weeks, read more about our postgraduate pre-sessional English course.
How to apply
Application deadlines
We operate a staged admissions process for this course with selection deadlines throughout the year.
If you do not receive an offer in a particular round, you will either be notified that your application has been unsuccessful, or we will carry your application forward to be considered in the next round.
Please see our How to Apply page for full details and the application deadlines for each stage.
This link takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
A January 2021 start for Data Science and Analytics is currently available.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Fees
- UK: £11,250 (total)
- International: £25,500 (total)
Read more about paying fees and charges.
Brexit
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.
For fees information for international taught postgraduate students, read Masters fees.
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Find out more at Masters funding overview.
Career opportunities
There is increasing demand for individuals who can manage and control the way data is used. These individuals require an understanding of computer science and mathematics as well as a range of sector specific skills.
The emerging era of ‘big data’ brought about by the digital technology revolution shows no signs of abating. With the modern world producing ever-growing amounts of new information, data scientists will become increasingly important to help governments, businesses, researchers, NGOs and many other organisations make sense of it all.
Careers support
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
You’ll have access to the wide range of careers resources and support from your Careers Service. You’ll have the chance to attend industry presentations, book appointments with qualified careers consultants and take part in employability workshops and webinars.
Our annual STEM Careers Fairs provide further opportunities to explore your career options with some of the UKs leading employers.
Find out more about the range of services we offer on the Careers Service website and visit MyCareer.leeds.ac.uk once you have registered as a student to access one to one support, events and job vacancies.