Everything about QGIS
In the QGIS GeoAgent course, you’ll learn how to perform geographic analyses and manage workflows in QGIS using natural language, without any programming. You’ll work with the GeoAgent plugin, in combination with a Large Language Model such as ChatGPT or Google Gemini, to perform GIS tasks like layer management, selections, filters, and analyses quickly and intuitively.
Want to learn how to perform GIS analyses and control workflows using natural language, without having to program or endlessly click through menus? In the QGIS GeoAgent course, you’ll learn how to work more efficiently and intuitively in QGIS with the help of AI assistance. You’ll discover how to literally communicate with your GIS project to perform analyses, manage layers, and gain insights.
QGIS is a powerful open-source GIS platform for analyzing and visualizing geographic data. In this course, you’ll build on your QGIS fundamentals and learn to work with the GeoAgent plugin, an innovative tool that drives QGIS functionality via Large Language Models (LLMs) such as Google Gemini. You’ll learn how GeoAgent translates commands in plain language into concrete GIS actions and how to maintain control over the process.
Working with GeoAgent goes beyond mere automation. You’ll learn how AI support helps you with exploratory analysis, data preparation, performing standard operations, and accelerating repetitive GIS tasks. Understanding what’s happening remains central: GeoAgent supports your workflow but does not replace your GIS knowledge.
In QGIS GeoAgent, you explicitly integrate AI into your daily GIS workflow. Whether you’re working on spatial analysis, monitoring, education, data exploration, or decision-making—this course shows how AI boosts your productivity and makes GIS more accessible, entirely within QGIS and without writing a single line of code.
You’ll work with open-source software (supplemented with external AI services), follow a hands-on approach, and develop skills that align directly with the future of GIS. Technically innovative, yet clearly explained and focused on both understanding and application.
Please note! Basic proficiency in QGIS is a prerequisite for this course. If you do not yet have this, we recommend taking the QGIS Basic Course first.
In this course, you’ll learn step-by-step how to use GeoAgent as a smart GIS assistant within QGIS. You’ll start with the basics: what AI agents are, how GeoAgent works, and how the connection to an LLM is established.
Next, you’ll get hands-on experience with:
Through clear explanations and practical exercises, you’ll learn how to apply GeoAgent responsibly and effectively within professional GIS projects.
This course demonstrates how AI and GIS converge in daily practice. While AI often remains abstract, this course introduces you to a concrete and immediately applicable form of AI support in QGIS.
You will learn, among other things:
The course is designed for practical and self-directed learning, with a focus on transparency, control, and applicability.
This course is intended for GIS users who want to work more efficiently and are interested in AI-supported GIS workflows. Do you work in spatial analysis, the environment, infrastructure, planning, research, education, or consulting? Then this course offers immediate added value.
You don’t need programming knowledge, but you do need a basic understanding of QGIS. Do you already have experience with geographic data and want to spend less time clicking and more time analyzing? Then QGIS GeoAgent is a logical next step.
On Day 1, you’ll be introduced to GeoAgent and the role of AI assistance within QGIS. You’ll learn what AI agents and Large Language Models are, how GeoAgent works, and how to connect it to an external AI model (such as Google Gemini). The focus is on understanding, configuration, and safe use.
You’ll get hands-on experience installing and configuring the GeoAgent plugin and learn how natural language is converted into concrete GIS actions. You’ll perform simple but common GIS tasks using text commands, such as layer management, selections, filters, and basic analyses. There’s a strong emphasis on transparency: what exactly does GeoAgent do, and how do you verify the results?
By the end of Day 1, you will be able to:
Day 1 focuses on getting familiar with GeoAgent and the responsible use of AI in daily GIS tasks.
On Day 2, you’ll take it a step further and learn how to use GeoAgent for more complex workflows and analytical support. The focus shifts from individual tasks to combining multiple steps and streamlining entire GIS workflows.
You’ll work with realistic scenarios in which GeoAgent is used for exploratory analysis, data preparation, and support with spatial issues. You’ll also learn how to refine prompts, how to set up repeatable workflows, and where the limits of AI assistance lie. Attention is given to quality, interpretation, and the responsible use of AI in professional environments.
By the end of Day 2, you will be able to:
Day 2 focuses on applying, deepening, and integrating GeoAgent into professional GIS workflows.
Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.
GeoAgent is particularly well-suited for speeding up everyday GIS tasks such as layer management, selections, filters, buffers, and simple analyses in QGIS. Typical applications include exploratory spatial analysis, data preparation, quick checks of datasets, and supporting analysis workflows in the fields of the environment, spatial planning, infrastructure, and education.
GeoAgent is not a substitute for substantive GIS analysis, but rather a supportive tool. For complex projects, GeoAgent primarily assists with data preparation, performing standard steps, and exploring scenarios. The final analysis, interpretation, and quality control always remain the responsibility of the GIS specialist.
The course is relevant for a wide range of applications, such as environmental and climate monitoring, spatial planning, infrastructure projects, education, research, and consulting. Whenever there are many repetitive GIS tasks or a need for quick insights, GeoAgent can boost productivity.
GeoAgent uses a Large Language Model, such as ChatGPT or Google Gemini, to translate natural-language commands into GIS actions. The AI does not perform analyses “on its own,” but rather helps to control existing QGIS tools. This keeps the process transparent and verifiable, which is essential for professional use.
Yes, a basic understanding of QGIS is required. To acquire this, please take the QGIS basic training course.
