Why study this course?
Data drives modern decision鈥憁aking in business, finance, science, healthcare, government, and beyond. This course equips you with the tools to understand, analyse and communicate data effectively, preparing you to handle real鈥憌orld challenges with clarity and integrity.
You will gain a blend of theoretical knowledge and practical experience, learning how to interpret complex datasets, design effective models, and use industry鈥憇tandard tools throughout the entire data science workflow. You will also develop the ability to think critically about the societal and ethical implications of data鈥慸riven systems, a skill increasingly essential for responsible data professionals.
This online programme allows you to study flexibly, choosing from MSc, PGDip or PGCert pathways, and progressing at a pace that fits your life.
On this Data Science online course, you will:
- study research methods in data science, gaining insight into contemporary challenges and emerging trends
- learn core data mining techniques, from foundational theory to practical applications
- master data visualisation, including how to design compelling visuals and verify that they communicate accurately and ethically
- use industry鈥憇tandard tools to complete the full data science lifecycle, from data acquisition and cleaning to modelling, deployment and monitoring
- develop skills in optimisation and large鈥憇cale data handling, learning how to model and simulate complex data鈥慸riven systems
- build adaptability and critical judgement, preparing you to navigate new technologies, shifting methodologies and ethical considerations in a fast鈥慹volving field
Add more value to your degree
Students receive complimentary access to the Mediation Training Theory online course, a self鈥憄aced programme that builds valuable conflict鈥憆esolution and communication skills. These are increasingly important in collaborative data鈥慸riven environments, where clear dialogue and problem鈥憇olving support successful project outcomes.
Teaching
Lectures, seminars, tutorials and practical work.
Assessment
A mix of coursework exercises, presentations and tests.
Dissertation project
MSc students will submit a software artefact and a detailed description of its context in the area of study.
Schedule
You will access modules and components at a pace and on a timetable that suits your work and study environment.
Modules
Those studying towards an MSc take the compulsory modules and one optional module.
Those studying for a PGCert take four modules, while those studying for a PGDip take eight modules.
Course information may change. Module information and course content, teaching and assessment may change each year and after you have accepted your offer to study at the University of 58吃瓜. We display the most up-to-date information possible, but this could be from a previous academic year. For the latest module information, see the module catalogue.
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Compulsory modules
- Complex systems modelling and simulation: introduces a range of techniques and their applications to different classes of problems, with a practical focus on modern network-based models and simulation.
- Data and Information Visualisation: focuses on the question of how to utilise visual representations to make information accessible for exploration and analysis.
- Data-Driven Systems: is an advanced research-focused module that presents the foundations of distributed systems and techniques that process data.
- Discrete Optimisation: covers the theory, tools and technologies developed and used to solve problems in Integer Programming and Combinatorial Optimisation.
- End-to-End Machine Learning: focuses on using python packages to perform end-to-end data-driven analyses.
- Machine Learning Algorithms: covers the essential theory and algorithms, including mathematical foundations, and methodological approaches, using a variety of regression, classification and unsupervised approaches.
- Programming in Python: introduces and revises modelling, design and implementation in Python.
Optional modules
- Numeric Optimisation: takes linear algebra and optimisation as the primary topics of interest and solutions to machine learning problems as the applications of this of the resulting tools, techniques and algorithms.
- Research methods in Data Science: introduces the skills necessary for the planning, data gathering, data analysis and dissemination stages of Data Science research.
Dissertation project
In addition, students will submit a dissertation in Data Science, comprising of a detailed software artefact that implements and evaluates a workflow and a detailed description of the artefact and its context in the area of study. This module involves regular one-to-one contact with the Academic Supervisor.
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- Complex systems modelling and simulation: introduces a range of techniques and their applications to different classes of problems, with a practical focus on modern network-based models and simulation.
- Data and Information Visualisation: focuses on the question of how to utilise visual representations to make information accessible for exploration and analysis.
- Data-Driven Systems: is an advanced research-focused module that presents the foundations of distributed systems and techniques that process data.
- Discrete Optimisation: covers the theory, tools and technologies developed and used to solve problems in Integer Programming and Combinatorial Optimisation.
- End-to-End Machine Learning: focuses on using python packages to perform end-to-end data-driven analyses.
- Machine Learning Algorithms: covers the essential theory and algorithms, including mathematical foundations, and methodological approaches, using a variety of regression, classification and unsupervised approaches.
- Numeric Optimization: takes linear algebra and optimization as the primary topics of interest and solutions to machine learning problems as the applications of this of the resulting tools, techniques and algorithms.
- Programming in Python: introduces and revises modelling, design and implementation in Python.
- Research methods in Data Science: introduces the skills necessary for the planning, data gathering, data analysis and dissemination stages of Data Science research.
What it will lead to
Careers
Data science is one of the fastest鈥慻rowing job types worldwide. Graduates from this programme thrive in roles where analytical thinking, responsible data use and strong technical skills are essential.
Typical careers include:
- data scientist
- machine learning engineer
- data analyst
- business intelligence analyst
- quantitative researcher
- cybersecurity data specialist
- health and bioinformatics analyst
- environmental and conservation data modeller
- intelligence and risk analyst
- data visualisation specialist
With the ability to adapt to new tools and interpret complex data responsibly, you will be prepared for today’s roles and for data鈥慸riven careers still to come.
Elevate your career
Graduates from the School of Computer Science work in a wide variety of data roles, including:
- Lloyds Banking Group
- Microsoft
- Securities and Futures Commission (Hong Kong)
- UK Civil Service
Further your education
Many graduates of the School of Computer Science continue their education by enrolling in PhD programmes at St鈥疉ndrews.
Go your own way
Our offers training and start-up support, gives you access to expert mentors and an investor network, as well as one-to-one advice to help you realise your commercial potential.
Why 58吃瓜?
Wherever you are, you can take 58吃瓜 with you. Online Masters at the University of 58吃瓜 combine all the benefits of studying at one of the world's oldest and best universities, with all the advantages of flexible, personalised learning.
Alumni
Whether you join us online or in person, when you graduate you become a member of the University's worldwide alumni community. Benefit from access to alumni clubs, the Saint Connect networking and mentoring platform, and careers support.
“I really enjoy the Data Science programme 鈥� the flexible online learning format makes it easy to study alongside full-time work. The materials are excellent, the lecturers are approachable and give detailed feedback on assignments. It鈥檚 a challenging and rewarding experience.”
- Frankfurt, Germany
Entry requirements
For entry onto the MSc: A 2.1 undergraduate Honours degree in any subject from the UK or the equivalent international qualification. If you studied your first degree outside the UK, see the international entry requirements.
We will also consider applicants who do not have an undergraduate degree. In these circumstances we expect candidates to have at least five years of relevant professional learning. The Admissions team will holistically assess your application and determine the best route of entry for you. In some cases, this may be onto the PGCert in the first instance, from which students who attain a certain level in their modules will have the opportunity to progress to a full Masters degree.
Students are also required to have a desired level of English language proficiency. See English language tests and qualifications.
Application requirements
- A CV that includes your personal details with a history of your education and employment to date.
- A personal statement explaining why you have applied for this course, how it relates to your personal or professional ambitions, and how your academic and professional background show you have the skills needed to work effectively at postgraduate level.
- One original signed academic reference, or an employment reference if you are unable to provide an academic reference.
- Academic transcripts and degree certificates.
For more guidance, see supporting documents and references for postgraduate taught programmes.
English language proficiency
If English is not your first language, you may need to provide an English language test score to evidence your English language ability. See approved English language tests and scores for this course.
Fees and funding
Fees for September and October 2026:
£1,500 per 15 credits with an estimated total fee of £18,000
Scholarships and funding
Scholarships, bursaries and discounts can be awarded based on financial need, academic achievements, and even on where you live. Unlike a student loan, you don't have to pay the money back.
To support you through your studies, 58吃瓜 offers a number of scholarships and collaborates in various funding schemes designed to support you financially. Students starting online studies at Masters level can apply for scholarships of up to £6000 towards the course fees.
You may be eligible for the:
Current and former members of the UK armed forces may be eligible for funding from the Ministry of Defence Enhanced Learning Credit Scheme (ELCAS).
Start your journey
Legal notices
Admission to the University of St Andrews is governed by our Admissions policy
Information about all programmes from previous years of entry can be found in the .
Curriculum development
As a research intensive institution, the University ensures that its teaching references the research interests of its staff, which may change from time to time. As a result, programmes are regularly reviewed with the aim of enhancing students' learning experience. Our approach to course revision is described online.
Tuition fees
The University will clarify compulsory fees and charges it requires any student to pay at the time of offer. The offer will also clarify conditions for any variation of fees. The University鈥檚 approach to fee setting is described online.
Page last updated: 8 June 2026