Introduction
The programme covers machine learning, big data analytics, data visualisation, and data management, ensuring graduates are well-prepared for careers in data science. We welcome graduates from a wide range of academic backgrounds who are looking to take advantage of the growing demand for data scientists across almost every industry sector today including finance, health, government, retail and manufacturing.
Start in January or September
This programme is available to start in either January or September.
This programme is also available to study online.
Study Information
Study Options
- Learning Mode
- On Campus Learning
- Degree Qualification
- MSc
- Duration
- 12 months or 16 months
- Study Mode
- Full Time
- Start Month
- January or September
- Location of Study
- Aberdeen
Recent advances in data science, such as big data, predictive analytics, and AI technologies including ChatGPT and Bard AI are revolutionising the way organisations automate their processes, predict future trends, and engage with customers. However, 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 are not only highly skilled in a wide range of statistical and data analysis tools but who can go beyond statistics to gain real insights from data.
The MSc Data Science programme is specifically designed to address this challenge. We go beyond classical statistics and data analysis to teach you how to apply logical thinking, machine learning and computer algorithms to come up with solutions to problems faced across many academic disciplines and industry sectors.
The multidisciplinary and multisector focus of the MSc Data Science also means we welcome applications from a wide range of academic or professional backgrounds, including science, technology, engineering and medicine as well as the humanities, 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 the industry are covered. You will gain proficiency in the use of Wolfram Mathematica and learn the programming fundamentals that underpin languages such as Python and R.
By the end of this programme, you will have developed the mathematical, computational and communication skills needed to produce meaningful insights that organisations can use to improve their performance.
Available Programmes of Study
- MSc
-
Data Science
Qualification Duration Learning Mode Study Mode Start Month LocationMSc 12 months On Campus Learning Full Time September Aberdeen MoreProgramme Fees
Fee information Fee category Cost EU / International students £26,250 Tuition Fees for 2025/26 Academic Year UK £12,200 Tuition Fees for 2024/25 Academic Year Stage 1
Compulsory Courses
- Getting Started at the University of Aberdeen (PD5006)
-
This course, which is prescribed for all taught postgraduate students, is studied entirely online, takes approximately 5-6 hours to complete and can be taken in one sitting, or spread across a number of weeks.
Topics include orientation overview, equality and diversity, health, safety and cyber security and how to make the most of your time at university in relation to careers and employability.
Successful completion of this course will be recorded on your Enhanced Transcript as ‘Achieved’.
- Introduction to Programming (PX5007)
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15 Credit Points
This course teaches programming in high level languages and in particular the Wolfram Language (Mathematica). It will introduce all areas of this powerful language, including symbolic and numerical calculations and simulations, links to other high level languages such as R and Python, links to database languages mySQL and Mongo.
We will show how Wolfram Language allows computation to be applied to many areas of data analysis, and modelling. This allows us to gain deep insight into systems.
- Data Visualisation (PX5019)
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15 Credit Points
Visualising the outcome of a data analysis is critical to communicate the results. In this course we will study standard and cutting edge visualisation techniques to make sense of data, and present it in a compelling, narrative-focused story.
Presenting and visualising data and reporting on the result of an analysis are a crucial skill when making sense of data.
- Image Analysis (PX5023)
-
15 Credit Points
Nowadays a large volume of data is stored in form of images. This course introduces the tools needed to analyse images and extract information from them, including aspects of image enhancement, filtering, segmentation, morphological analysis and image classification based on convolutional neural networks.
- Introduction to Python and R (PX5026)
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15 Credit Points
In this course we will introduce Python and R for the MSc Data Science. This will include common packages used for data science and we will discuss typical programming constructs used in data science.
Stage 2
Compulsory Courses
- Advanced Statistics and Special Applications (PX5504)
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15 Credit Points
In this module we will discuss advanced and cutting-edge statistical tools and techniques.
Some of the topics covered are likelihood, advanced hypothesis testing, outlier detection, data imputation, bootstrap, nonparametric regression and mixed effect models.
- Introduction to Data Science (PX5508)
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15 Credit Points
The goal of this course is to introduce the student into the field of data science. You will improve your data literacy, understanding the different types of existing data and data structures, and the kind of problems that can be solved using it. You will learn the tools and techniques necessary to obtain the data, store it and manipulate it. You will learn tools and techniques to preprocess it and prepare it for analysis, statistical characterization and visualization. Then, you will be introduced to simple modelling techniques aimed at providing answers for the problems you want to solve. The final lectures are dedicated to introduce the MySQL and Mongo relational and non-relational databases, respectively.
- Machine Learning (PX5509)
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15 Credit Points
In this course we will discuss modern methods of machine learning, such as decision trees, regression, Markov models, Bayesian approaches, Nearest Neighbours, random forests, support vector machines and neural networks.
Great emphasis will be given to the actual application of all these methods to small and large data sets.
- Statistics and Time Series Analysis (PX5510)
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15 Credit Points
This is an introductory course in statistics and statistical methods for data analysis.
We will introduce descriptive statistics, ANOVA, GLMs, correlations, spectra, wavelets, etc.
This will allow us to perform typical analysis that underlie most modern data science questions.
Stage 3
Compulsory Courses
- Data Science Project (PX5901)
-
60 Credit Points
This is a project course for the MSc in Data Science. Students will be given a data science project, which will be supervised by one member of staff. Students will conduct research on that topic in an independent manner.
Students will have to deliver a presentation halfway through the project and hand in a report about the results at the end of the project. This will be followed by an oral examination of the submitted report.
MSc 16 months On Campus Learning Full Time January Aberdeen More
We will endeavour to make all course options available. However, these may be subject to change - see our Student Terms and Conditions page.
Fee Information
Additional Fee Information
- Fees for individual programmes can be viewed in the Programmes section above.
- In exceptional circumstances there may be additional fees associated with specialist courses, for example field trips. Any additional fees for a course can be found in our Catalogue of Courses.
- For more information about tuition fees for this programme, including payment plans and our refund policy, please visit our Tuition Fees page.
Scholarships
Self-funded international students enrolling on Postgraduate Taught (PGT) programmes for January 2025 will receive one of our Aberdeen Global Scholarships, ranging from £3,000 to £8,000, depending on your domicile country. Learn more about these Aberdeen Global Scholarships here.
From September 2025 all eligible self-funded international Postgraduate Masters students will receive an £8,000 scholarship. Learn more about this Aberdeen Global Scholarship here.
To see our full range of scholarships, visit our Funding Database.
How You'll Study
Learning Methods
- Individual Projects
- Lectures
- Research
- Seminars
Why Study Data Science?
- This programme equips you with the essential data analysis and computational thinking skills needed to extract knowledge and insights from data.
- Aimed at students from a wide range of academic backgrounds, including science, technology, engineering and medicine (STEM) but also business, arts and the humanities.
- Designed in collaboration with industry partners, including Wolfram Research, which means the algorithms, tools and workflows required by industry are extensively covered.
- 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.
- There has been a huge increase in demand for data specialists across almost every industry, from energy and manufacturing to healthcare and cybercrime. This recent LinkedIn Jobs on the Rise report listed Data Engineer as one of the fastest-growing jobs in the UK.
- The University of Aberdeen has a strong history and worldwide reputation in computing science, in particular around Data Science, Natural Language Generation and Artificial Intelligence and is home to the research success of ARRIA NLG - the global leader in the field of natural language generation (NLG).
- From agriculture and archaeology to medicine and geosciences, our researchers are utilising data and AI across many fields to further research and improve lives. Browse the project summaries in our Interdisciplinary Research Project Database to find out more about the critical role data and artificial intelligence have to play in advances spanning many disciplines.
- The University of Aberdeen is a member of the Turing University Network, a network of UK universities engaged in cutting-edge teaching and research in data science and AI.
Entry Requirements
Qualifications
The information below is provided as a guide only and does not guarantee entry to the University of Aberdeen.
2:2 (lower second class) Honours degree or equivalent in any subject will be considered.
Please enter your country to view country-specific entry requirements.
English Language Requirements
To study for a Postgraduate Taught degree at the University of Aberdeen it is essential that you can speak, understand, read, and write English fluently. The minimum requirements for this degree are as follows:
IELTS Academic:
OVERALL - 6.5 with: Listening - 5.5; Reading - 5.5; Speaking - 5.5; Writing - 6.0
TOEFL iBT:
OVERALL - 90 with: Listening - 17; Reading - 18; Speaking - 20; Writing - 21
PTE Academic:
OVERALL - 62 with: Listening - 59; Reading - 59; Speaking - 59; Writing - 59
Cambridge English B2 First, C1 Advanced, C2 Proficiency:
OVERALL - 176 with: Listening - 162; Reading - 162; Speaking - 162; Writing - 169
Read more about specific English Language requirements here.
Document Requirements
You will be required to supply the following documentation with your application as proof you meet the entry requirements of this degree programme. If you have not yet completed your current programme of study, then you can still apply and you can provide your Degree Certificate at a later date.
- CV
- an up-to-date CV/Resumé
- Degree Certificate
- a degree certificate showing your qualifications
- Degree Transcript
- a full transcript showing all the subjects you studied and the marks you have achieved in your degree(s) (original & official English translation)
- Personal Statement
- a detailed personal statement explaining your motivation for this particular programme
Aberdeen Global Scholarship
Eligible self-funded Postgraduate Taught (PGT) students will receive the Aberdeen Global Scholarship. Explore our Global Scholarships, including eligibility details, on our dedicated pages.
January 2025 September 2025Careers
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.
According to Prospects.ac.uk, entry-level salaries for Data Scientists range from £25,000 to £30,000. With a few years' experience you could expect to earn £40,000 to £60,000, while experienced, high-level, data scientists or contractors can earn upwards of £60,000, in some cases reaching more than £100,000.
Graduates of this programme will be well placed to pursue careers such as:
- Business Intelligence Analyst
- Data Architect
- Data Mining Engineer
- Data Scientist
This recent LinkedIn Jobs on the Rise report listed Data Engineer as one of the fastest-growing jobs in the UK.
Our Experts
- Programme Leader
- Professor Marco Thiel, The University of Aberdeen
Information About Staff Changes
You will be taught by a range of experts including professors, lecturers, teaching fellows and postgraduate tutors. However, these may be subject to change - see our Student Terms and Conditions page.
Get in Touch
Contact Details
- Address
-
Student Recruitment & Admissions
University of Aberdeen
University Office
Regent Walk
Aberdeen
AB24 3FX