2023/24 Taught Postgraduate Programme Catalogue

MSc Data Science (Statistics) (online)

100% online

Total credits: 180

Entry requirements:

Education and Work Experience:
A bachelor’s degree with a 2:1 (hons) in a subject containing a substantial mathematical and statistical component.

Alternatively, a degree with a 2:2 (hons) in a subject with a substantial mathematical component plus three years of work experience in a role with substantial use of statistical models and associated reporting.

English Language requirements:
All applicants will need to have GCSE English Language at grade C or above, or an appropriate English language qualification.

Students for whom English is not their first language must meet the University of Leeds entry criteria for English language, IELTS 6.5 overall, with no less than 6.0 in any component.

TOEFL iBT (Test of English as a Foreign Language Internet-Based Test) or TOEFL iBT Home Edition at 88 overall with no less than 19 in listening, 20 in reading, 22 in speaking and 21 in writing. Please note that we do not accept TOEFL MyBest scores and expect candidates to have met the relevant requirements from a single TOEFL test.

Other accepted minimum qualifications for English Language skills are outlined in the current Taught Postgraduate Admissions policy.

Where necessary, students will be expected to improve their English further during the programme by making use of the online English tuition support that we provide.

School/Unit responsible for the parenting of students and programme:

Digital Education Service

Examination board through which the programme will be considered:

Digital Education Service

Programme specification:

The MSc Data Science (Statistics) is the result of a partnership between leading academics in the School of Mathematics and the Leeds Institute for Data Analytics (LIDA). The programme provides students with theoretical knowledge and practical skills desirable in a range of sectors where understanding of data analytics and statistical techniques are central.

The programme will provide students with a solid foundation in key topics in data science, including programming, statistical learning and machine learning as well as re-enforcing key concepts in statistics. Students will then explore more advanced topics in statistics such as multivariate statistics, linear models, Bayesian statistics and statistical computing. In each topic there will be opportunities for you to put theory into practice through selected examples.

In the latter part of the programme students will use research from LIDA, and others, to work on projects in innovative areas such as AI, health informatics, urban analytics, statistical and mathematical methods, and visualisation and immersive technologies. Experience in these areas will help you prepare for the future of data science.

Graduates would be well placed to be employed in many sectors including healthcare, retail, finance and government.

Students will normally study one module at a time.

Year1 - View timetable

[Learning Outcomes, Transferable (Key) Skills, Assessment]

In your first year you will typically study six 15 credit modules.

Compulsory modules:

You will study the following three Foundation modules in your first year of study.

Optional modules:

You will study three out of the six Development modules in your first year of study.

Year2 - View timetable

[Learning Outcomes, Transferable (Key) Skills, Assessment]

In your second year you will typically study the remaining six 15 credit modules.

Compulsory modules:

You will study three Advanced modules in your second year of study.

Optional modules:

You will study the remaining three out of six Development modules in your second year of study.

Last updated: 17/04/2024 12:02:42

Disclaimer

Browse Other Catalogues

• Undergraduate module catalogue
• Taught Postgraduate module catalogue
• Undergraduate programme catalogue
• Taught Postgraduate programme catalogue

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD