Data Science (part time) MSc

School of Science and Engineering

Developed specifically to meet the needs of those currently working in IT, you will be able to gain a formal qualification whilst continuing to work

Date of entry

January 2022

Start date

January 2022


24 months

Study mode

Part Time


Online / Dundee City Campus

From the apps you use on your phone to the items you buy from the supermarket, data is being gathered every second of every day. With so much data to analyse, data scientists are in high demand throughout the commercial and academic industries.

You will learn to store, manipulate and analyse big data effectively by implementing powerful and innovative methods to transform vast amounts of data into actionable insights.

You will explore areas such as logical and physical models of analytical systems, data mining, and machine learning.

The course is specifically designed with career development in mind. It provides additional skills and knowledge for those currently working in IT and related areas.

You will complete two one-week blocks of intensive teaching on campus each year with the rest of your time spent learning from home, developing your skills, knowledge, and understanding of data science. Therefore, you will be able to gain a formal qualification whilst continuing to work.

Unlike other courses in this field, you do not need an advanced understanding of mathematics, as the course focuses on how to apply the principles of data science to the data you are working with rather than just the equations.

You will be taught by industry experts currently working in the field, increasing your understanding of real-life situations you could face in your career.

“Transformed my life! It was hard work but the content was so absorbing and fabulously well delivered. Part-time was great as I could continue working and juggle the other parts of my life - with help from my family, of course! I was lucky enough to get a role as Data Scientist but it has also opened other opportunities I never thought possible at this stage in my career.”

Amanda Styles, MSc Data Science (part time) graduate

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