Online Learning Module

Prepare yourself through a short, interactive module.

The online learning module helps you prepare for the Design Challenge Events organised by our partner countries during this project phase, but you can also follow it as a stand-alone learning experience.

Recommended for participants who are new to Design Thinking or STEAMSS challenges. Whether you are a lecturer looking to bring Challenge Based Learning into your classroom, a student preparing for an upcoming challenge, or an industry professional curious to learn more about this approach, this module is your starting point.

Welcome!

Self-paced Beginner

Welcome! On this page, you can explore the interactive online learning module. This module helps you prepare for the Design Challenge Events organised by our partner countries during this project phase, but you can also follow it as a stand-alone learning experience.

Whether you are a lecturer looking to bring Challenge Based Learning into your classroom, a student preparing for an upcoming challenge, or an industry professional curious to learn more about this approach, this module is your starting point.

Fast, hands-on lessons with practical examples

Perfect for lecturers, students, and industry professionals

Build confidence before joining a STEAMSS challenge

Start learning.

Are you ready to learn something new?

Start course

#energy #pv #python #dashboards Beginner • 6h • Self-paced

How to prepare a design challenge event.

12:43

Learn how inverter telemetry is structured, common issues (gaps, outliers), and how to prepare it for analysis.

Learning objectives

Understand PV telemetry fields and sampling intervals.
Identify common data quality issues and quick fixes.
Prepare a clean dataset for time-series analysis.

Tip: pair this with PV Monitoring with Python notebooks.

Creators

Chloë Mentens

GS Course Creator

Katrien Dehaese

GS Course Creator

00:02
Welcome! In this lesson we’ll look at how inverter data is structured…
02:18
Here are the most common fields: timestamp, pac, e_total, temp…
05:40
To handle gaps, we first resample to a fixed interval and mark missing values…
10:12
Outliers often appear during sunrise/sunset. Let’s cap by quantiles as a quick win…