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Learn Python for data science — NumPy, Pandas, Matplotlib

Structured Python data science path from intermediate level to real-world projects. Guided by Py — an AI tutor that tracks your exact concept mastery and adapts every explanation.

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Python Data Science curriculum

Prerequisites

Python Fundamentals Review

Variables, loops, functions, lists — make sure your foundations are solid before NumPy.

Module 1

Introduction to NumPy

Arrays, vectorised operations, array indexing, and why NumPy is faster than Python lists.

Module 2

Pandas DataFrames

Reading data, Series vs DataFrames, selecting rows/columns, filtering and sorting.

Module 3

Data Cleaning

Handling missing values, duplicates, data types, outliers — the real 80% of data work.

Module 4

Data Manipulation

Groupby operations, merging datasets, pivot tables, applying functions across DataFrames.

Module 5

Matplotlib & Visualisation

Line charts, bar charts, scatter plots, histograms — communicating data visually.

Module 6

Descriptive Statistics

Mean, median, variance, correlation — understanding your data before modelling it.

Module 7

Real Data Science Project

End-to-end project: ingest a real dataset, clean it, analyse it, and present insights.

Frequently asked questions

Do I need Python experience before starting data science?

Yes — Python Fundamentals is a prerequisite. Start with Fundamentals (free), then upgrade to Pro for the Data Science path. Py will assess your readiness during onboarding.

What Python libraries does the data science path cover?

NumPy, Pandas, and Matplotlib. Statistical concepts are introduced throughout. Machine learning (Scikit-learn, TensorFlow) comes in the Advanced specialisations.

Is Python the best language for data science?

Yes — Python dominates data science and machine learning. It has the most mature library ecosystem and is used in the vast majority of data science job roles worldwide.

How is this different from a Pandas tutorial on YouTube?

Py knows which concepts you're finding difficult and adjusts accordingly. If DataFrames are confusing you, Py won't move on until you've got it. YouTube plays the same video regardless.

Related guides

Start with Python Fundamentals — it's free

Build the Python foundation you need before diving into data science. Free to start, no credit card. Upgrade to Pro when you're ready for the Data Science path.