Program Overview

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Introduction to the Geospatial Data Science & AI MSc Program

The University of Glasgow offers a Master of Science degree in Geospatial Data Science & AI, a program designed to equip students with advanced geospatial, analytical, programming, and AI/Machine Learning skills. This interdisciplinary program focuses on the application of geospatial data science and artificial intelligence to real-world problems, particularly in environmental, urban, and socio-technical domains.

Program Description

The MSc in Geospatial Data Science & AI is a taught postgraduate program that combines foundational knowledge in Geographic Information Systems (GIS), cartography, spatial statistics, and remote sensing with specialized skills in geospatial artificial intelligence (GeoAI), machine learning applications, and big geospatial data analytics. The program is highly applied and research-led, utilizing real-world datasets, modern software tools (such as Python, QGIS, and ArcGIS), and reproducible workflows. A key component of the program is the MSc project, which allows students to work on an independent research project or industry-aligned dissertation under the supervision of academic staff, often in collaboration with external partners.

Why Choose This Program

Several factors make this program attractive to potential students:

• GeoAI-first curriculum: It is one of the first programs in the UK to foreground GeoAI, including vision-language models and trustworthy AI practice, grounded in core geospatial concepts.
• Strong geospatial foundations: The program builds robust skills in GIS, cartography, spatial statistics, geospatial fundamentals, and Earth observation/remote sensing.
• Flexible pathways and options: Students can tailor their learning through various options, including Big GeoData Analytics, Remote Sensing of the Environment, Environmental Statistics, Web and Mobile Mapping, Geospatial Data Infrastructures and Land Administration, and Applied GIS, with suggested pathways in Geospatial Data Science and Computational Environmental Sciences.
• Hands-on, project-based learning: The program emphasizes learning through labs, computer practicals, and project work using real geospatial datasets, with continuous assessment mirroring professional practice.
• Modern tools and infrastructures: Practical experience is gained with Python, open-source and commercial GIS, modern data infrastructures, and reproducible workflows highly valued by employers and research organizations.
• Addressing recognized skills gaps: The program directly responds to national and international calls for graduates who can integrate environmental or geoscience knowledge with advanced data management, spatial analysis, and visualization, and environmental statistics.
• Supportive, research-rich environment: Students learn from staff actively engaged in Geospatial Data Science, GeoAI, Earth Observation/Remote Sensing, and other environmental applications, within a School that holds an Athena Swan Silver Award and has a strong commitment to inclusive, student-centered active learning.

Program Structure

The MSc in Geospatial Data Science & AI is delivered predominantly through computer-based practical classes, laboratories, and workshops, supported by lectures, seminars, and labs/tutorials. Learning is strongly applied and interactive, with most courses assessed through coursework along the learning journey.

Semester One

• Academic and Professional Skills for GES PGT: Introduction to academic and professional skills necessary for postgraduate study in Geospatial Data Science.
• Geospatial Fundamentals: Core concepts in geospatial data and analysis.
• Introduction to Statistics for Environmental Analysis: Statistical methods for analyzing environmental data.
• Principles of GIS: Fundamentals of Geographic Information Systems.
• Principles of Cartographic Design & Production: Introduction to cartography and map production.

Semester Two

Core Courses

• Introduction to Geospatial Artificial Intelligence (GeoAI): Explores foundation models, spatially explicit AI models, representation learning, and applications of deep learning for various geospatial tasks.
• Machine Learning Applications for Earth Systems Problems: Develops understanding and skills of ML techniques based on environmental and Earth-system data.

Optional Courses

Students choose from a range of optional courses to tailor their degree, including but not limited to:

• GES_Spatial Data Analytics
• Remote Sensing of the Environment
• Environmental and Ecological Statistics (Level M)
• Modelling of Landscape Evolution
• Analytical Methods in Geoscience
• Applied GIS

These options allow students to shape their degree toward one of two indicative pathways or create a bespoke route:

• Geospatial Data Science track: Emphasizing geospatial data infrastructures, applied GIS, and web/mobile mapping.
• Computational Environmental Science track: Emphasizing remote sensing, environmental statistics, and geospatial data infrastructures.

Summer - MSc Project

The MSc project is an independent research project or industry-aligned dissertation on a topic of the student's choice, supervised by a member of academic staff and often using real datasets from external partners. This project allows students to consolidate the knowledge and skills gained throughout the program and produce a substantial piece of work to showcase to employers or support applications for PhD study.

Career Prospects

Graduates of the MSc Geospatial Data Science & AI are equipped to work at the interface of geospatial technologies, data analytics, and visualization, and AI. Typical roles include:

• Geospatial / GeoAI Data Scientist
• Earth Observation or Remote Sensing Analyst
• Spatial Data Engineer or GIS Developer
• Urban or Transport Analytics Specialist
• Environmental or Climate Risk Modeller
• Location Intelligence / Geo-visualisation Specialist

Graduates find opportunities in environmental consultancies, government agencies, national mapping organizations, transport and utilities companies, tech firms and start-ups, as well as finance, insurance, and climate/fintech sectors where location-based risk and asset modeling are increasingly important. The program also provides a strong foundation for PhD study in geospatial data science, GeoAI, Earth observation, environmental informatics, and related fields.

Fees & Funding

Tuition Fees

• Home & RUK: Full-time fee is Ł12,960, and part-time fee is Ł1,440 per 20 credits.
• International & EU: Full-time fee is Ł31,050.

Fee Status

Guidance on fee status is available.

Deposits

International and EU applicants are required to pay a deposit of Ł2,000 when an offer is made. Terms and conditions for deposit refunds are specified.

Additional Fees

• Fee for re-assessment of a dissertation (PGT programme): Ł370
• Submission of thesis after deadline lapsed: Ł350
• Registration/exam only fee: Ł170

Funding Opportunities

The University of Glasgow offers various scholarships, including:

• ScottishPower Master Scholarship
• The Bseisu- University of Glasgow Scholarship
• University of Glasgow CoSE-UGM Alumni Scholarship
• University of Glasgow African Excellence Award
• University of Glasgow Caribbean Excellence Award
• World Changers Glasgow Scholarship
• Global Leadership Scholarship
• GREAT Scholarships 2026
• The Humanitarian Scholarship
• Alumni Discount
• Other external and internal funding opportunities.

Entry Requirements

• Academic Requirements: A 2.2 Honors degree (or non-UK equivalent) in a relevant field such as Geography, Earth or Environmental Science. Other subjects with relevant work experience may also be considered.
• English Language Requirements: For applicants from non-English speaking countries, the University sets a minimum English Language proficiency level, which can be met through various English language tests (e.g., IELTS, TOEFL, Pearsons PTE Academic) or by completing a degree in a majority-English speaking country.

How to Apply

To apply for the MSc Geospatial Data Science & AI, applicants must submit their application online, including supporting documents such as official degree certificates, academic transcripts, English language proficiency tests (if required), and a reference letter. The application process involves several rounds with specific deadlines for international and EU applicants, as well as a final deadline for home applicants.

Application Deadlines

• International & EU Applicants: Application rounds with deadlines from October to July, with decisions made on a rolling basis.
• Home Applicants: Final deadline is August.

Related Programs

The University of Glasgow offers a range of related postgraduate programs in Data Science & Artificial Intelligence and Geographical & Earth Sciences, including:

• Advanced Statistics [MSc]
• Computational Geoscience [MSc]
• Computing Science [MSc]
• Data Analytics [MSc/PgDip/PgCert: Online distance learning]
• Climate & Environmental Science [MSc]
• Earth Futures: Environments, Communities, Relationships [MSc]
• Geoinformation Technology & Cartography [MSc/PgDip/PgCert]

These programs cater to various interests and career goals, providing students with a comprehensive education in their chosen field.