University of St Andrews - Online
MSc / PGDip / PGCert in Data Science - OnlineOnline United Kingdom
DURATION
1 up to 3 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
31 Aug 2025
EARLIEST START DATE
Aug 2025
TUITION FEES
GBP 18,000 *
STUDY FORMAT
Distance Learning
* for MSc part-time | GBP 12,000 - for PGDip part-time | GBP 6,000 - for PGCert part-time
Introduction
Develop advanced data science skills, including machine learning and data analysis that are essential for careers in many data-driven sectors, through a flexible, online MSc.
Develop core skills in data science essential to successful careers in many data-driven sectors.
Why study this course?
Gain skills in demand by global, commercial, financial and research institutions.
This course covers a mix of practical and theoretical topics essential to careers in many data-driven sectors. You will learn how to approach real-world data problems and apply your skills in critical thinking, problem solving, and analysis.
The Data Science course is an online self-paced programme, with options to study for MSc, PGCert and PGDip.
- Study research methods in data science and understand contemporary issues in the field.
- Discover methods of data mining, from the underlying core theory to practical understanding.
- Learn how to create compelling information visualisations and how to verify visual displays of data.
- Use industry-standard computing resources to employ the full data science workflow from data acquisition and processing, through model development and selection, to final deployment and maintenance.
- Study optimisation techniques, how to curate and use large quantities of data, and how to model and simulate complex systems of data.
Gallery
Admissions
Scholarships and Funding
We are committed to supporting you through your studies, regardless of your financial circumstances.
Successful entrants starting online studies at Master's level can apply for scholarships of up to £6000 towards the course fees.
- St Leonard's funding opportunities
- Graduate discount (15% off tuition fees)
Curriculum
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.
MSc
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
It 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 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 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.
PGCert, PGDip
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
It 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 Optimisation
Takes linear algebra and optimisation as the primary topics of interest and solutions to machine learning problems as the applications 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.
Program Tuition Fee
Career Opportunities
Data Science is one of the world's fastest-growing job types. Qualified data scientists are highly sought after in a wide range of sectors, including business and finance, intelligence services, cybersecurity, healthcare, conservation, the arts, and more.
Why study at University of St Andrews - Online
Wherever you are, you can take St Andrews with you. Online Master's at the University of St Andrews combine all the benefits of studying at one of the world's oldest and best universities, with all the advantages of flexible, personalised learning.
Program delivery
Teaching
Lectures, seminars, tutorials and practical work.
Schedule
You will access modules and components at a pace and on a timetable that suits your work and study environment.