Data Scientist Career Path
- 1Python for Data Science
- 2Data Analytics: Statistics & Data Visualization
- 3Introduction to Machine Learning
- 4Introduction to Deep Learning & Neural Networks
- 5MLOps: Deploying Machine Learning & Deep Learning Models
The language as a data practitioner uses it, not as a software engineer does.

Python for people who will use it to analyse things. No classes, no decorators, no async. Instead: the data structures you actually touch daily, pandas until you trust it, and the habit of reading an error message to the end — which is what separates someone who can keep going from someone who stops at the first red line.
Read a free lesson: Why Python for DataEvery module and lesson in this track. Lessons marked free are open to everyone; the rest open once you own the track.
Every lesson in this track, with summariesWhy Python, what to install, and how to read an error.
Lists, dicts, tuples, sets — and when to reach for which.
Load, clean, group, join. The four things a working day is made of.
The real one, from a lesson — it runs in your browser. No account needed.
This track is part of a larger path. Buy the whole path as a bundle and every track in it costs 40% less.