Artificial Intelligence for Geodata
Today, it's impossible to ignore terms like artificial intelligence, machine learning, deep learning, computer vision, NLP, data science... But what do these terms really mean, and how can these technologies be applied to geodata to help solve your spatial challenges? How do you determine whether AI is the right solution for your specific problem? Join this one-day training session to explore the concepts, tools, typical project workflows, and common pitfalls of applying AI to geodata.
Practical information:
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In this course, you will learn:
The basic concepts, tools, development process, and evaluation criteria needed to assess how GeoAI can help solve your spatial problems.
Topics covered include:
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Key concepts such as artificial intelligence, machine learning, and GeoAI
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A taxonomy of AI techniques
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Fundamental approaches like supervised, unsupervised, and reinforcement learning
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Machine learning tools: frameworks, applications, and server/cloud infrastructure
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Designing and evaluating AI workflows
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The Machine Learning Canvas: assessing feasibility and planning your AI project
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GeoAI use cases in domains such as computer vision, planning, prediction, and pattern recognition
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A practical overview of GeoAI through a comprehensive set of real-world examples
This training will be conducted in English.