Python is the language most data scientists work in every day, and a small set of libraries do most of the heavy lifting. This module takes you from Python fundamentals to the three libraries you will use in almost every project: NumPy, Pandas, and Matplotlib.
You'll start with the core language: variables, data structures, control flow, and functions. Then you'll move to NumPy for fast numerical arrays, the same vectors and matrices from the previous module, now in code. Next comes Pandas for loading, filtering, grouping, and cleaning tabular data, followed by Matplotlib for turning that data into plots.
With these tools in hand, you'll be ready to track your work properly in Version Control & Notebooks, the next module in this course.
A full beginner course from freeCodeCamp that starts with programming basics and the Python language, then moves into NumPy, Pandas, and Matplotlib with hands-on practice.
How NumPy arrays work and why they beat plain Python lists: creating arrays, indexing and slicing, math and statistics, reshaping, and boolean masking.
A hands-on Pandas course built around projects: DataFrame basics, filtering and sorting, data cleaning, and grouping and joining real datasets.
An introduction to Matplotlib: building simple line plots, then customizing titles, labels, colors, and styles so your charts are easy to read.