Python & Machine Learning

A practical Python-to-ML pathway for the working professional: programming fundamentals, data libraries, then modern machine learning with a focus on shipping useful models.

Language

Python fundamentals, then pandas and NumPy for real data work.

Analytics

SQL plus matplotlib/plotly for exploration and communication.

ML Core

Scikit-learn and training/serving basics; transformers as the modern frontier.

Script daily with Python before touching ML libraries – fluency comes first.
Do an end-to-end project (collect, clean, model, serve) to marry the pieces.
Learn to evaluate honestly: precision/recall and concept drift matter more than accuracy.
Extend into MLOps (Docker, cloud, monitoring) to differentiate from the crowd.

Take the Pivot Quiz – find your best next role.