Pick a role. Follow a path.

Python + SQL + Spark, with the warehouse knowledge to glue them together.

1. 1 Python (Core, OOP, Engineering)
2. 2 SQL (full track)
3. 3 Pandas
4. 4 PySpark
5. 5 MLOps basics

Build, train, and deploy models — the role most teams actually need.

1. 1 Python
2. 2 NumPy
3. 3 Pandas
4. 4 Math for ML
5. 5 Machine Learning
6. +2 more

Ship LLM-powered products. Async Python, RAG, agents, evals.

1. 1 Python (async, Pydantic, FastAPI)
2. 2 SQL (essentials)
3. 3 Generative AI
4. 4 Agentic AI

From SQL to statistical rigor to communicating results that change decisions.

1. 1 Python
2. 2 Pandas
3. 3 Visualization
4. 4 SQL
5. 5 Math for ML
6. +1 more

Docker, CI/CD, MLflow, serving, Kubernetes. The glue that runs production ML.

1. 1 Python
2. 2 MLOps
3. 3 PySpark

Math, PyTorch, transformers — for people building the next architecture.

1. 1 Math for ML
2. 2 Deep Learning
3. 3 Generative AI