Masters | Postgraduate Course - Data Analytics MSc, PG Dip Course Details within Strathclyde Business School

Strathclyde Business School
Course Fees
£9,900 (UK/EU), £18,750 (International)
Start Month(s)
Contact Name
SBS Postgraduate Admissions
(0)141 553 6105/4590
Data Analytics MSc, PG Dip

Study Details

MSc/PGDip: 12 months full-time

Our MSc in data analytics is designed to create rounded data analytics problem-solvers.

This course focuses on the uses of data analytics techniques within business contexts, making informed decisions about appropriate technology to extract knowledge from data and understanding the theoretical principles by which such technology operates.

You'll gain a comprehensive skill set that will enable you to work in a variety of sectors using a blended learning approach that combines theory, intensive practice and industrial engagement.

Strathclyde's MSc in data analytics is unique by bringing together essential skills from three departments, Management Science, Mathematics & Statistics, and Computer & Information Sciences (CIS), in order to address the needs of a fast-growing industry.

This collaboration avoids the narrow interpretation of this subject offered by competitor institutions and presents significant opportunities for businesses to recruit data analytics experts with a high-level expertise and knowledge.

Module details

Compulsory classes

  • Big Data Fundamentals
  • Big Data Tools & Techniques
  • Data Analytics in R
  • Business & Decision Modelling
  • Optimisation for Analytics
  • Data Analytics in Practice
  • Dissertation in Data Analytics

Optional classes
Students are required to choose 40 credits worth of elective classes, and at least from two departments. All optional classes take place in Semester 2.
Department of Computer & Information Sciences

  • Database Fundamentals
  • Evolutionary Computation for Finance 1
  • Evolutionary Computation for Finance 2
  • Legal, Ethical & Professional Issues for the Information Society
  • Fundamentals of Machine Learning for Data Analytics

Department of Mathematics & Statistics

  • Financial Econometrics
  • Bayesian Spatial Statistics
  • Networks in Finance
  • Mathematical Introduction to Networks

Department of Management Science

  • Stochastic Modelling for Analytics
  • Business Simulation Modelling
  • Risk Analysis & Management
  • Business Information Systems

Entry Requirements


Second-class Honours degree, or equivalent, in mathematics, the natural sciences, engineering, or economics/finance. Applications from those with other degrees are also encouraged if you have demonstrated a good grasp of numerical/quantitative subjects.


Minimum of a pass degree or equivalent in an appropriate subject. Subject to performance diploma students may transfer from the diploma course to the MSc.

Student Destinations

The aim of the MSc in data analytics is to develop graduates who can use data analytics technology, understand the statistical principles behind the technologies and understand how to apply these technologies to solve business problems.

Graduates will be able to bridge the various knowledge domains that are relevant for tackling data analytics problems as well as being able to identify emerging themes and directions within data analytics. Graduates will display abilities across the three component disciplines