Course overview
Almost everything happens somewhere, and location data, from satellites, sensors, GPS, and maps, holds patterns that ordinary tables miss. Geospatial analytics extracts those patterns, and predictive modeling uses them to anticipate where things will happen next, from demand and risk to environmental change. Together they support decisions across planning, resources, logistics, and beyond.
This course covers geospatial analytics and predictive modeling end to end. It runs from the fundamentals through GIS tools and techniques, predictive modeling with geospatial data, AI in geospatial analytics, and the governance, ethics, and future of geospatial data. It is built for analysts, planners, and technical professionals who want to work with location data confidently and responsibly.
Why this matters
Decisions about where to build, where risk concentrates, or how resources move are far better when grounded in spatial evidence than in intuition. As geospatial data grows cheaper and more abundant, the advantage goes to those who can analyze it.
Geospatial skills matter because location adds a dimension that transforms analysis: a pattern invisible in a spreadsheet can be obvious on a map. Professionals who can apply GIS and predictive modeling to spatial problems make sharper, better-grounded decisions. This course builds that capability, including the ethics that responsible use requires.
What you will be able to do afterwards
By the end of the course, participants should be able to:
- Explain what geospatial analytics is and where it applies.
- Use core GIS tools and techniques.
- Build predictive models with geospatial data.
- Apply AI to geospatial problems.
- Address governance and ethics in geospatial data.
Course outline
Unit 1: Introduction to geospatial analytics
The course opens with the field and its data.
- What geospatial analytics is.
- Sources of geospatial data.
- Spatial concepts and coordinate systems.
- Documented applications.
Unit 2: Tools and techniques in GIS
This unit covers the working toolkit.
- GIS software and data layers.
- Spatial analysis methods.
- Mapping and visualization.
- Data quality and preparation.
Unit 3: Predictive modeling with geospatial data
This unit covers looking ahead spatially.
- Spatial prediction concepts.
- Modeling location-based outcomes.
- Validating spatial models.
- Worked modeling examples.
Unit 4: AI in geospatial analytics
This unit covers advanced methods.
- Machine learning on spatial data.
- Image and remote-sensing analysis.
- Combining AI with GIS.
- Limits and pitfalls.
Unit 5: Governance, ethics, and future of geospatial data
The final unit covers responsible use.
- Privacy in location data.
- Data governance and quality.
- Ethical use of geospatial analytics.
- Emerging trends.
How the course is delivered
The course is led through structured explanation, worked examples, documented case studies, and group discussion of how spatial data is analyzed and modeled. Participants examine maps, datasets, and model outputs and work through the interpretation and ethical questions involved. For the geoscience application in more depth, it connects to GIS and Spatial Data Analysis for Geoscientists.
Who should attend
This course suits analysts and data professionals, planners and GIS staff, geoscientists and environmental professionals, and technical staff who work with location data. It works for those new to geospatial analytics and for experienced staff who want to add predictive modeling and AI. Comfort with data helps but advanced statistics are not required.
About EuroQuest International Training
EuroQuest International Training was founded in 2015 by a team with more than 25 years of combined experience in professional training. The institute has delivered over 1,000 courses to more than 15,000 participants, and is headquartered in Bratislava, Slovakia, with training hubs in Dubai, London, Barcelona, Istanbul, Vienna, Paris, and Geneva. Courses are designed and reviewed by practitioners and updated to reflect current practice in each field.
Frequently asked questions
Do I need GIS experience to attend?
No. The course introduces GIS tools and techniques from the ground up before moving to predictive modeling and AI, so it suits newcomers as well as those with some experience.
Does it cover AI and machine learning?
Yes. A dedicated unit covers machine learning on spatial data, image and remote-sensing analysis, and combining AI with GIS, including its limits.
Is it tied to a particular industry?
No. Geospatial analytics applies across planning, environment, logistics, resources, and more, and the course draws examples from several fields.
Related courses
- Remote Sensing and GIS in Geosciences
- Big Data Analytics and Predictive Modeling
- Geostatistics and Data Analytics in Geology
- Remote Sensing Applications in Resource Management
Register for this course
To reserve a place or ask about scheduling and city options for the Geospatial Analytics and Predictive Modeling course, use the registration and enquiry options on this page and the EuroQuest team will follow up with the details you need.
All Course Dates & Locations
26 dates · 16 cities · Oct 2026 – Jun 2027