Data Science, MSc

University of Aberdeen

There is an increasing demand for data scientists across all industry sectors, from healthcare and tech to finance, retail and beyond. This programme enables graduates of various disciplines to take advantage of the growing career opportunities in this field, by teaching the essential Computational Thinking (CT) and data analysis skills needed by employers today.

Over the last 5 years, there has been an enormous increase in demand for Data Scientists across almost every industry sector, from tech and finance to energy, retail, healthcare and cybersecurity.

As the volume, diversity and complexity of data being gathered continue to increase, the key challenge facing organisations today is how to make sense of data, and more importantly how to use data to inform business decisions.

To solve this problem, companies need data scientists who not only are highly skilled in a wide range of statistical and data analysis tools, but who can go far beyond classical statistics and machine learning to gain real insights from data. The MSc Data Science programme is specifically designed to address this challenge.

Unlike many other data science programmes, this MSc goes beyond statistics and big data, to use a Computational Thinking (CT) approach to data science, one that applies logical thinking, sequencing and algorithms to create solutions to problems across many disciplines and industries.

The multidisciplinary focus of the programme also means that it is open to qualified applicants from across a wide range of academic backgrounds, including science, technology, engineering and medicine (STEM), but also business and social sciences.

This programme has been designed in collaboration with industry partners, including Wolfram Research, to ensure that the algorithms, tools and workflows required by industry are covered. You will also gain proficiency in the use of Wolfram Mathematica programme.

The overall objective of this programme is to create experts who can combine their mathematical modelling and programming skills with an ability to work effectively in multidisciplinary teams to extract knowledge and insights from data.