About this module
This opening session sets the frame for the whole course. We look at how AI models differ from the physically-based and statistical models most water professionals already know, walk through the data-to-decision workflow that every case study in this course follows, and set up the Python / Google Colab environment you'll use throughout. By the end, you'll have trained and interpreted your first model — a simple linear regression on a real hydrological dataset.
How AI tools fit into how you learn here
This course treats AI tools as more than the subject matter — they're part of the method. Every module runs through notebooks where you're expected to prompt, question and iterate with an LLM tutor: turning a vague hydrological question into working Python code, and using the model's explanations to check your own understanding rather than copy its output blindly. We come back to this explicitly across the course — what makes a good prompt for a technical task, where LLMs help and where they mislead, and how to build a repeatable workflow around them instead of a one-off trick. Week 1 is where you get comfortable with that loop for the first time.
Topics covered
- ✓ Why AI differs from traditional physically-based and statistical models
- ✓ Framing an environmental problem as a data-science question
- ✓ The data-to-decision workflow: from raw sensor readings to actionable insight
- ✓ Setting up Python and Google Colab — the environment used all course
- ✓ Your first hands-on model: simple and multiple linear regression on a hydrological dataset
- ✓ Prompting an LLM tutor to explain, debug and extend your first notebook
Optional: MATLAB Self-Paced Track
Provided by our technology partner MathWorks as a free, self-paced complement to this week's session. If you're new to MATLAB, start with the introductory course below before this week's course — and budget around 20–30% more time than the stated duration.
MATLAB Online access and GPU credits are provided free to registered participants during the course period (August 2026).
Where to find the rest of the material
The slide deck and Colab notebook for this module are being finalized and will be linked directly from this page before the module opens in August 2026. Once published, you'll find:
- The full session slide deck (PDF)
- The Colab notebook for the regression exercise
- A short list of readings on AI vs. traditional hydrological modelling
Questions in the meantime? Reach the course team via the enquiries section on the main course page.