MSc Applied Data Science and Modelling

1 Years On Campus Masters Program

University of Exeter

Program Overview

The MSc Applied Data Science and Modelling at the University of Exeter equips you with the analytical, computational and modelling skills needed to make sense of real‑world data and mathematical models to tackle major societal and environmental challenges such as sustainability and systems complexity. It’s a one‑year, research‑informed master’s that’s perfect for students who enjoy quantitative problem‑solving and want to apply data science in interdisciplinary settings including industry, public sector or research.

Curriculum Structure

Term 1 – Core Foundations
In the first term you’ll build essential skills through modules like Fundamentals of Data Science and Computational Modelling and Simulation, giving you a solid grounding in data analysis, mathematical modelling techniques and simulation tools. These foundational modules are designed to ensure you’re confident working with complex datasets and mathematical representations of real‑world phenomena from day one.

Term 2 – Advanced Methods and Interdisciplinary Application
During your second term you’ll deepen your expertise with Trends in Data Science and Artificial Intelligence, explore interdisciplinary problem solving through Tackling Sustainability Challenges using Data and Models, and choose from optional modules such as Applied AI and Control or sustainability‑focused topics like Transforming Energy Systems and Low Carbon Vehicles and Transport. This term blends state‑of‑the‑art data science methods with practical applications that sit at the intersection of modelling, AI and real environmental or societal contexts.

Term 3 – Capstone Project
Your final term is dedicated to the Data Science and Modelling Dissertation, an advanced independent project where you apply everything you’ve learned to a substantial research or applied challenge under academic supervision. This project is your chance to explore a topic of real interest, from predictive analytics and optimisation to sustainability modelling.

Focus areas:
Data science fundamentals, computational modelling and simulation, artificial intelligence and trends in data science, interdisciplinary sustainability problem solving and advanced independent research.

Learning outcomes:
Graduates will emerge with strong analytical and modelling capabilities, advanced data handling and computational skills, the ability to design and implement mathematical models for complex systems, and experience applying these skills to real‑world challenges such as sustainability and public‑sector or industry problems.

Professional alignment (accreditation):
While the programme does not list a specific professional accreditation, its curriculum is developed in close consultation with academic research and industry trends, preparing you for roles in data analytics, modelling and decision support across sectors that value applied mathematical and data‑driven expertise.

Reputation (employability rankings):
The University of Exeter is ranked Top 20 in the UK for Mathematics (The Times and The Sunday Times Good University Guide 2026), and this interdisciplinary MSc is rooted in a strong research environment that is respected by employers in analytics, sustainability and technical sectors.

Experiential Learning (Research, Projects, Internships etc.)

This programme is designed around active engagement with real data and mathematical models, so you won’t just learn concepts you’ll put them into practice tackling real challenges linked to sustainability, environment and complex systems. Based at the Penryn Campus in Cornwall, you’ll be part of an interdisciplinary environment where mathematics meets science and engineering, working alongside researchers and students from related fields. Throughout the year you’ll develop hands‑on experience with state‑of‑the‑art data science and computational modelling techniques, culminating in an advanced project where you apply your skills to a real‑world problem.

Here’s how experiential learning is built into the programme:

Practical & Experiential Features of the MSc Applied Data Science and Modelling

Advanced Data Science & Modelling Project: In Term 3, you complete a substantial independent dissertation project where you apply the data science and modelling skills you’ve learned to investigate a real problem building your experience in research, analysis and communication.
Interdisciplinary Inquiry Module: Through Tackling Sustainability Challenges using Data and Models, you’ll work on real sustainability issues in a team setting, developing solutions with peers and using mathematical modelling tools directly.
Core Computational & Data Science Skills: Core modules like Fundamentals of Data Science and Computational Modelling and Simulation give you practical training in modern computational methods and software preparing you for data‑intensive work.
Trends in Data Science and AI: This module exposes you to state‑of‑the‑art methods and gives hands‑on experience with techniques central to current industry and research practice.
Optional Specialist Learning: You can choose optional modules (e.g., Applied AI and Control, Transforming Energy Systems, Low Carbon Vehicles) that allow you to deepen your domain‑specific expertise through project work and applied learning.
Collaborative Environment: You’ll join a vibrant Graduate School of Environment & Sustainability community, working with peers across disciplines and engaging with real interdisciplinary challenges in seminars and group work.
Industry & Sector Engagement: The programme encourages collaboration with industry partners, charities and public sector organisations, giving you opportunities to apply your skills beyond purely academic tasks.

Progression & Future Opportunities

Graduate outcomes summary: Graduates of the MSc Applied Data Science and Modelling at the University of Exeter go on to pursue careers where advanced data science skills meet real‑world problem‑solving particularly in sustainability, analytics and interdisciplinary science. Typical roles include Data Scientist in environmental/tech sectors, Sustainability Modeller, AI/ML Specialist with analytical focus and Quantitative Researcher:

Progression & Future Opportunities:

University services to help you employ: Exeter’s Career Zone offers personalised one‑to‑one career guidance, CV and interview workshops, industry networking opportunities and access to employer contacts across data, sustainability and science sectors.
Skills aligned with market demand: You graduate with strong data science, modelling and computational skills that employers value for evidence‑based decision‑making and tackling complex sustainability challenges. The UK’s data analytics sector is forecast to grow rapidly, offering broad opportunities.
University–industry connections: The degree emphasises interdisciplinary collaboration with science, engineering and public‑sector partners, giving you experience applying models and analytics to real problems and opening professional pathways.
Long‑term academic recognition: As part of a programme led by internationally recognised researchers—and situated at Exeter’s Penryn Campus, a hub for environmental mathematics and sustainability—your qualification gains credibility with employers and academic institutions alike.
Graduation outcomes: Graduates are prepared for roles where they can interpret complex data, build models for sustainability and inform strategic decisions across sectors such as environmental consultancy, clean tech, government analytics and data science.

Further Academic Progression:
After completing the MSc, you could continue with doctoral research (PhD) in areas like computational modelling, environmental data science, climate systems analysis or interdisciplinary applied mathematics, which can position you for advanced research or academic careers. You may also pursue professional certifications in data science, AI or sustainability analytics to strengthen your specialist expertise and leadership prospects.