Skip to content
CoursesTrack
1 free lesson3 simulations

Python for Data Science

The language as a data practitioner uses it, not as a software engineer does.

Level
Fundamentals
Modules
3
Lessons
4
Total time
55 min
Python for Data Science
Tools you'll use
  • Python
  • NumPy
  • pandas

After this track you can

  • Read and write enough Python for day-to-day data work
  • Use lists, dicts and comprehensions without looking up an example
  • Load, clean and join data with pandas
  • Read a traceback down to the line that is actually wrong

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 Data

What you'll learn, module by module

3 modules · 4 lessons

Every 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 summaries
  1. 01

    Why Python, what to install, and how to read an error.

    1 free lesson2 lessons20 min1 simulation
    1. 1Why Python for DataFree
    2. 2Reading a Traceback to the End
  2. 02

    Lists, dicts, tuples, sets — and when to reach for which.

    1 lesson15 min1 simulation
    1. 1Lists and Dicts
  3. 03

    Load, clean, group, join. The four things a working day is made of.

    1 lesson20 min1 simulation
    1. 1DataFrames and Cleaning

Try a simulation from this track

The real one, from a lesson — it runs in your browser. No account needed.

Save with a career-path bundle

This track is part of a larger path. Buy the whole path as a bundle and every track in it costs 40% less.

Career-path bundle40% off

Data Scientist Career Path

  1. 1Python for Data Science
  2. 2Data Analytics: Statistics & Data Visualization
  3. 3Introduction to Machine Learning
  4. 4Introduction to Deep Learning & Neural Networks
  5. 5MLOps: Deploying Machine Learning & Deep Learning Models
Career-path bundle40% off

AI Engineer Career Path

  1. 1Python for Data Science
  2. 2Introduction to Deep Learning & Neural Networks
  3. 3LLMs, Prompt Engineering & Context Engineering
  4. 4Building AI Agents: Harness Engineering
  5. 5MLOps: Deploying Machine Learning & Deep Learning Models
  6. 6Computer Vision with Deep Learning
  7. 7Natural Language Processing (NLP)
Lifetime access
$9
Buy