Data Science and Data Analytics

Data Science and Data Analytics are related subjects but they have distinct differences. Data Science is a broad term for developing and using scientific methods, processes and algorithms to analyse large sets of raw and structured data such as big data. Data scientists look for answers to questions that businesses and organisations don’t know, or establish solutions to problems that haven’t yet been thought of. Data Analytics is more focused and concentrates on carrying out statistical analysis on existing data sets. It can be used to measure events in the past, present, or future. Data Analytics tends to be more business and strategy focused.

Core skills needed in Data Science and Data Analytics include programming, machine learning, statistics and statistical analysis. Artificial Intelligence (AI) is also becoming important due to advances in data driven AI.

Hear from Dr Kevin Swingler, Senior Lecturer, explaining how the University of Stirling’s Data Science courses will equip you to play a vital role in the future of data.

Data Science and Data Analytics courses

Courses labelled are available for online study only.

Undergraduate courses
CourseStart date
BSc (Hons) Data ScienceSeptember 2024, January 2025
BSc (Hons) Graduate Apprenticeship in Data ScienceSeptember 2024
Postgraduate courses
CourseStart date
MSc Artificial IntelligenceSeptember 2024, January 2025
MSc Big DataSeptember 2024, January 2025
MSc Big Data (Online)May 2024, October 2024, February 2025, May 2025
MSc Business AnalyticsSeptember 2024, January 2025
MSc Data Science for BusinessSeptember 2024, January 2025
MSc Finance and Data AnalyticsSeptember 2024
MSc Financial Technology (FinTech)September 2024, January 2025
MSc Marketing AnalyticsSeptember 2024, January 2025
MSc Mathematics and Data ScienceSeptember 2024, January 2025
MSc Social Statistics and Social ResearchSeptember 2024, January 2025
Professional Doctorate Data ScienceSeptember 2024, January 2025
CPD and short courses
CourseStart date
Machine LearningJune 2024
Python for Representing and Manipulating DataJune 2024

Scholarships

We offer a variety of scholarship and funding options to help you finance your studies at the University of Stirling.

Undergraduate scholarships

See more undergraduate scholarships

Postgraduate scholarships

See more postgraduate scholarships

Why study Big Data and Data Science at the University of Stirling

Graduate careers in Data Science and Data Analytics

As a graduate in Data Science or Data Analytics you’ll be equipped for roles such as Data Analyst, Data Scientist, Data Engineer, Enterprise Architect, Machine Learning Scientist and Business Intelligence Developer. A wide range of sectors need data specialists including:

  • ecommerce and retail
  • digital technologies
  • robotics
  • healthcare
  • financial technology (Fintech)
  • legal technology (Lawtech)
  • automotive (self-driving cars)
  • cyber security
  • energy and utilities
  • public sector

Partnerships and industry

We are a member of The Data Lab, which is an Innovation Centre with the aim of developing data science talent and skills required by the industry in Scotland. We also work with the Scottish Informatics and Computing Science Alliance (SICSA).

Our MSc Data Science for Business degree is endorsed by The Data Lab and is the first in Scotland to be developed with inputs from SAS, a global leader in business analytics solutions, leading financial services organisation HSBC and The Data Lab to ensure it meets industry needs

Data Science and Data Analytics research

Our team of academics from the department of Computing Science and Mathematics are involved in research in areas including complex systems modelling, computer vision, machine learning, optimisation and artificial intelligence.

See more about our Data Science and Intelligent Systems research.

Postgraduate research opportunities

Our Professional Doctorate Data Science is the first industrial doctorate of its kind, and is supported by The Data Lab.

See our PhD and MPhil opportunities in Computing Science and Mathematics including Data Science.