
The European energy market is a fast-moving, complex distributed system. Driven by massive amounts of data and external signals like the weather, shifts in supply and demand constantly ripple through the grid, affecting electricity prices in real time.
Your challenge? Treat the energy market like a puzzle made of data.
Dive into structured datasets of real spot prices and weather fundamentals to uncover meaningful patterns. Your goal is to build a working artifact-like a dynamic dashboard or visualization-that explores, abstracts, and explains the underlying dynamics of what truly moves the price.
Read the full case description, curiosity prompts, and evaluation criteria here https://www.kaggle.com/t/8c074f2bbd8943d0a4a836f5f4bfa6f6
The choice of tech stack is entirely up to you! Since you will be exploring structured datasets to build a working artifact-like a visualization, dashboard, or prediction model-tools suited for data analysis, machine learning, and frontend development (such as Python, R, SQL, JavaScript, or BI tools) will be your best friends.
Submissions will be evaluated qualitatively based on four core pillars:

How might we improve everyday university life for students and create a stronger sense of community and engagement? Your solution could explore areas such as supporting volunteer experiences, exploring new teaching formats, improving everyday student life, or facilitating community between international and Danish students.
Teams are encouraged to develop a concept, prototype, or solution that enhances the student experience.
As always, there will be 3D printers and hardware available for use. You may also leverage available data, or imagine how to create or obtain data to support your concept or prototype. Volunteers and lab staff will be available to assist with hardware and technical questions.
Judging will focus on the novelty of your hack, the clarity of your problem definition, and the strength of your argumentation for why your solution works and addresses the challenge.