Python Tutorial

Learn Python

Learn Python in eight stages — from your first script to the web, the cloud, AI applications and the data-science stack. Every example runs in the browser.

Start learning →185 lessons · 29 chapters

Stage 1

Stage 2

Modules & Packages

Importing Modules
The Standard Library
pip & Virtual Environments

Files & Errors

Reading & Writing Files
try / except
Raising Exceptions

Object-Oriented Programming

Classes & Objects
__init__ & Attributes
Methods
Inheritance
Dunder Methods
Properties

Working with Data

JSON In and Out
CSV and Tabular Files
Dates, Times and Time Zones
Money and Precision
Matching Patterns with re
Paths and Files
Validating at the Boundary
Reshaping Records

Code That Survives Contact

Testing with pytest
Fixtures and Test Data
Mocking the Network and the Clock
Logging Instead of print
Type Hints That Earn Their Place
Environments and Dependencies
Laying Out a Project
Designing Your Exceptions

Stage 3

Python on the Web

HTTP, from Python's Side
Calling an API
Authentication and Secrets
Retries, Backoff and Rate Limits
Paging Through a Large API
Serving Your First Endpoint
Routes, Parameters and Responses
Validating a Request Body
Talking to a Database
Configuration the Twelve-Factor Way
Errors a Client Can Act On
Uploads and Downloads

Stage 4

Doing Several Things at Once

Why Async Exists
async def and await
Running Many at Once
Twenty Calls in the Time of One
Timeouts and Cancellation
Threads, Processes or Async
Producers and Consumers
The Four Mistakes Everyone Makes

Stage 5

Cloud, Containers and Automation

Writing a Command-Line Tool
Configuration from the Environment
Structured Logs for an Aggregator
Packaging into a Container
Reproducible Installs
Running in CI
Talking to a Cloud SDK
Scheduled and Background Work
Shutting Down Cleanly
Health Checks and Metrics

Stage 6

Building with AI Models

Why Python Runs AI
Calling a Model API
Getting Structured Output
Streaming a Response
Rate Limits, Retries and Timeouts
Many Prompts at Once
Tokens, Context and Cost
Prompts as Code
Embeddings and Similarity
Retrieval: Finding the Right Context
Tool Calling
Testing Code That Calls a Model

Stage 7

Foundations for AI

Why Python for AI
The AI Ecosystem
Jupyter Notebooks
Setting Up Your Environment
AI vs Machine Learning vs Deep Learning

NumPy

Creating Arrays
Indexing and Slicing
Shape and Reshape
Vectorized Operations
Broadcasting
Aggregations
Random Numbers

pandas

Series
DataFrame
Reading CSV Files
Selecting and Filtering
Grouping and Aggregating
Handling Missing Data
Merging DataFrames
Applying Functions

Data Visualization

Matplotlib Basics
Line, Bar and Scatter Plots
Histograms and Distributions
Seaborn for Statistical Plots

Data Preparation

Cleaning Data
Encoding Categorical Data
Scaling and Normalization
Train/Test Split
Feature Engineering

Machine Learning Basics

Supervised vs Unsupervised
The scikit-learn API
Linear Regression
Logistic Regression
Evaluation Metrics

Classification & Clustering

Decision Trees
Random Forests
K-Nearest Neighbors
K-Means Clustering
The Confusion Matrix
Cross-Validation
Overfitting and Underfitting

Deep Learning Intro

What Is a Neural Network?
Tensors
Layers and Activations
A Tiny Keras Model
The Training Loop

Putting It Together

An End-to-End ML Workflow
Saving and Loading Models
Responsible AI
Next Steps

Stage 8

Advanced Python

Iterators & Generators
Decorators
Context Managers
Type Hints

Operators in Depth

Arithmetic, Floor & Power
Comparison Chaining
Identity vs Equality, and Membership
Bitwise Operators & Flags
The Walrus Operator :=
The Conditional Expression
Boolean Short-Circuiting
Unpacking with * and **
Operator Overloading with Dunders

Advanced OOP

Abstract Base Classes
Protocols & Structural Typing
Dunder Methods that Matter
@property — Computed Attributes
Class Methods & Static Methods
@dataclass
__slots__ — Leaner Objects
Multiple Inheritance & the MRO
Generic Classes with class Stack[T]

Pythonic Power

Decorators, End to End
Generators & yield
Context Managers & with
Advanced Comprehensions
Structural Pattern Matching
functools: lru_cache, partial & more
Type Hints & Generics