What this section is for¶
This section gives you the organisational, pedagogical and practical context for SDS320. It explains what the course is about, how the Jupyter Book supports your learning, how the semester is structured, how assessment works and where you can find help.
SDS320 is the final module of the Spatial Data Science minor. It builds on your previous work with spatial data, GIS, remote sensing and Python, and moves toward applied spatial analytics and data-driven modelling.
The course is project-driven. This means that the weekly topics should inspire from your own project. They are meant to help you define a feasible spatial question, select data and methods, implement an analytical workflow, evaluate results and communicate your findings.
How SDS320 works¶
SDS320 combines technical input, independent preparation, project labs, peer exchange and continuous project development.
In the weekly sessions, you will encounter selected concepts, tools and example workflows. These inputs are intended to support your own project work. Project-oriented parts of the course give you time to discuss ideas, receive feedback, troubleshoot technical problems and learn from the work of others.
Because the course follows a flipped classroom concept, the Jupyter Book is not just a collection of notes after class. You should use it before, during and after sessions.
What you should read first¶
Start with these pages:
Welcome — introduces the course and the project-driven learning approach.
How to use this book — explains how the Jupyter Book is organised.
Schedule — shows the weekly topics and project focus.
Assessment — explains how your work is assessed.
AI use and integrity — explains how AI tools may be used responsibly.
Resources — points you to course platforms, documentation and support.
Feedback — explains how you can help improve the course materials.
Syllabus — quick reference, if you want to look something up.
What to return to during the semester¶
You will probably return to the schedule regularly to check how weekly topics connect to project milestones.
You should revisit the assessment page when preparing your concept presentation, final presentation, report and repository.
The AI use and integrity page is important whenever you use AI tools for writing, coding, debugging or project planning.
The resources and feedback pages help you find support, ask useful questions and improve the course material for yourself and future students.
Key message¶
SDS320 is a course that provides you with the opportunity to develop your own spatial project. Your project should grow throughout the semester. The more steadily you define, test, revise, document and discuss your work, the easier it becomes to produce a clear results, a compelling report, a reproducible repository and a convincing final presentation.