Module library
Reusable building blocks that combine to create custom training programs.
Claude Code Setup
Install and configure Claude Code for AI-assisted development
Download materials
Clone the course repository with all exercises and resources
ENTSO-E Setup
Connect to Europe's official energy data source and run your first queries. You'll learn to adapt notebook templates to your own analysis cases — the foundation for all energy work in this course.
Install Git
Install and verify Git on macOS and Windows
Install Jupyter Lab
Install Python and Jupyter Lab on macOS and Windows
Install Miniconda
Download and configure Miniconda on macOS and Windows
Advanced environment setup
Install scikit-learn, SHAP and ML dependencies
Update materials
How to pull the latest updates to your course materials
Python help menus in VS Code
Use VS Code's built-in help to explore Python functions and modules
VS Code Setup
Install and configure Visual Studio Code for AI-assisted development
Data handling with pandas
Manipulate time series of prices, generation and consumption
Introduction to Python
Python basics: data types, variables, control flow, functions
PostgreSQL database integration
Query and load energy market data directly from Python
Excel export and report generation
Generate formatted multi-sheet reports with xlwings
Process automation and file handling
Move and organize files automatically, process data reproducibly
Integrating exercise
End-to-end exercise combining all modules
Reading and generating XML files
Read and generate XML files for energy market integration
Introduction to ML for energy
Machine Learning fundamentals applied to energy markets
Applied business project
End-to-end pipeline: predict day-ahead market prices
ML in production
Export models, automate predictions, integrate with databases
Model interpretability
Understand what drives predictions with SHAP and feature importance
Pattern detection & anomalies
Clustering, Isolation Forest and correlation analysis
Random Forest & Gradient Boosting
Build predictive models with scikit-learn
scikit-learn pipelines
Automate preprocessing, tuning and evaluation
Time series concepts
Temporal features and introduction to ARIMA-type models
AI agents as programming assistants
Use LLMs as technical copilots for code generation, optimization and validation
AI Energy Analytics
Instructor runs energy queries with the agent, then pauses to read and explain the code behind each step. Students learn what DataFrames are, how queries work, what visualizations do under the hood, and how to spot errors — shifting from vibe coding to code comprehension.
AI Energy Dashboard
Instructor builds a dashboard live following a structured workflow: first sketch what charts to show, then define the frontend structure, then implement with the agent, then iterate to polish. Design-first, not prompt-and-pray.
Claude Code Fundamentals
Master Claude Code - Anthropic's AI CLI that transforms how you write code. From running scripts to web scraping with MCP.
Use case demos & environment check
Live demos of what you will build and verify your setup works
Advanced demos & environment check
Live demos of ML predictions and anomaly detection
Need custom training?
Combine the modules you need to create a program tailored to your team.
Request information