Tools chain together: Python language → notebooks → pandas/NumPy → visualization → SQL warehouses → optional cloud ML platforms.
Local stack to install
python -m venv .venv— isolated environmentpip install jupyter pandas numpy matplotlib scikit-learnjupyter lab— interactive notebooks
Playground lessons use stdlib until you install packages locally.
Data locations
- CSV/Parquet files — pandas
read_*locally - SQL warehouses — query with SQL, load samples into pandas
- APIs — Python
requests+ JSON parsing
Version control
Track notebooks and scripts in Git—commit small, document data snapshots and random seeds for reproducibility.
Important interview questions and answers
- Q: Why venv?
A: Isolates project dependencies from system Python. - Q: Warehouse vs notebook?
A: Warehouse aggregates at scale; notebook explores samples and models.
Self-check
- Name three pip packages for a starter stack.
- Why Git for notebooks?
Tip: Create a venv and pip install jupyter pandas locally this week.
Interview prep
- venv?
Isolates pip packages per project.
- Warehouse role?
SQL aggregates at scale; notebooks explore samples.