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Data Science MSc, PGDip and PGCert

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Informatics

Course type

Taught

Course Summary

Learn how to apply technology to real world data science problems and gain an in depth understanding of emerging technologies, statistical analysis and computational techniques.

By studying this degree you will:

  • have the option to study one of the specialist pathways in Artificial Intelligence or Financial Technology
  • address skills required by data scientists to drive improvements in organisational performance
  • have the opportunity to create your own data analysis projects
  • earn a prestigious qualification that is valued across the globe.

How you study

You can study this online programme from anywhere in the world. The flexible approach to learning enables you to fit your studies around your commitments whilst providing the academic rigour and structure of an on-campus programme.

Modules are offered over two 22-week sessions each academic year. You choose which sessions to enter and how many modules to take in each session.

Assessment deadlines are outlined clearly in advance of the session.

The maximum number of modules you can study in one session is six, (or four plus the final project). You will also receive comprehensive learning materials and support from online tutors.

Career opportunities

Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government.

The benefits of our programme is flexible to address the skills shortage of data scientists who can use data to drive improvements to organisational performance. You will have the opportunity to gain highly-valued skills through the specialist pathways: MSc Data Science; MSc Data Science and Artificial Intelligence; MSc Data Science and Financial Technology.

Students can also exit with Pgdip and PgCert awards.

Different course options

Study mode

Online

Duration

1 year

Start date

OCT-20

Modules

Mathematics and Statistics for Data Science - Core
Machine Learning - Core
Data Programming in Python - Core
Big Data Analysis - Core
Data Visualisation - Core
Data Science Research Topics - Core
Final Project in Data Science

Tuition fees

UK fees
Course fees for UK / EU students

Band A: Independent web-supported student - £8000; Recognised Teaching Centre supported student - £4080 + teaching centre fee. Band B: Independent web-supported student - £12000; Recognised Teaching Centre supported student - £6800 + teaching centre fee.

Average for all Postgrad courses (per year)

£5,202

International fees
Course fees for non-UK / EU students

Programme fee varies by country (Please contact the University): The following fee as a guide for non-UK students: £12000 for Independent web-supported student; £6800 + teaching centre fee for Teaching centre supported student; Other fees extra.

Average for all Postgrad courses (per year)

£12,227

Entry requirements

Entry Route 1: To be eligible to register for any of the Data Science programmes, you must have the following: A bachelor’s degree (or an acceptable equivalent) in a relevant subject which is considered at least comparable to a UK second class honours degree, from an institution acceptable to the University. Relevant subjects include but are not limited to the following: Biomedical Statistics; Business Computing; Computer Science; Creative Computing; Data Science; Economics; Engineering; Finance; Games Programming; Machine Learning and Artificial Intelligence; Marketing and Finance; Mathematics and statistics; Physics. Entry Route 2: A bachelor’s degree (or an acceptable equivalent) in any subject which is considered at least comparable to a UK second class honours degree, from an institution acceptable to the University. In addition to the above, you will be required to complete an online preparatory course prior to registration. The online preparatory course, Foundations of Data Science: K-Means Clustering in Python, requires approximately 30 hours of study.