1. How to read the schedule¶
Each week combines a lesson topic with a project focus.
The lesson topic introduces a concept, method or workflow that may be useful for spatial data analytics. The project focus shows what kind of project development is expected around that time.
The course is designed so that your project develops gradually. You should use the weekly structure to make decisions, test ideas, receive feedback and improve your workflow.
2. Weekly programme¶
| Week | Date | Lesson topic | Project focus | Suggested project progress |
|---|---|---|---|---|
| 1 | 15 Sep | Course introduction | Project framework | Understand the course structure and collect first project ideas. |
| 2 | 22 Sep | Project planning | Project topic | Narrow down a possible topic and draft an initial spatial question. |
| 3 | 29 Sep | Data acquisition | Data & methods | Identify possible datasets and check whether they fit your question. |
| 4 | 06 Oct | Data preprocessing | Concept presentations | Prepare your concept presentation and test whether your data can be processed. |
| 5 | 13 Oct | Training data | Concept presentations | Clarify whether your project needs labels, masks, samples or validation data. |
| 6 | 20 Oct | Object detection | Data analysis | Start moving from project planning into implementation and analysis. |
| 7 | 27 Oct | Semantic segmentation | Data analysis | Continue analysis and check whether your method fits your data and question. |
| 8 | 03 Nov | Instance segmentation | Processing pipeline | Turn scattered code into a clearer processing pipeline. |
| 9 | 10 Nov | Image translation | Figures & visuals | Start developing figures, maps or visual comparisons for your results. |
| 10 | 17 Nov | Change detection | Storytelling | Connect your outputs to a clear project argument. |
| 11 | 24 Nov | Regression | Repository | Improve repository structure, reproducibility and documentation. |
| 12 | 01 Dec | Segment Anything | Final presentations | Present final project progress and receive final feedback. |
| 13 | 08 Dec | Satellite embeddings | Final presentations | Present final project progress and reflect on implementation decisions. |
| 14 | 15 Dec | Finale Grande | - | - |
3. Important project moments¶
Several weeks are especially important for project development:
Weeks 1–2: You move from broad project ideas toward a feasible topic.
Week 3: You check whether suitable data are available.
Weeks 4–5: Concept presentations help you receive feedback before most implementation work is completed.
Weeks 6–8: You move into data analysis and processing pipeline development.
Weeks 9–11: You work on figures, interpretation, storytelling and repository organisation.
Weeks 12–13: Final presentations focus on what you implemented, found and learned.
Final submission: The project report and repository must be submitted via the corresponding MS Teams assignment by Monday, 14 December 2026, at 17:00.
4. Flexibility¶
The programme may be adjusted during the semester depending on implementation progress, student needs, project progress and technical requirements.
This flexibility does not mean that project work can be postponed. It means that the course can respond to realistic project challenges while still expecting continuous progress.