Python with AI: Free Python Tutorial from Scratch

What you will learn

Course curriculum

Work through the chapters in order. Each one takes 20 to 40 minutes, and the sidebar tracks where you are.

Getting Started

1. 1
   Python Introduction: What Is Python and Why Learn It
2. 2
   Install Python and Set Up VS Code with an AI Assistant
3. 3
   Python Syntax: Indentation, Statements and Your First Program
4. 4
   Python Comments: Single-Line, Multi-Line and Docstrings
5. 5
   Python Variables: Naming Rules, Assignment and Types
6. 6
   Python Data Types: str, int, float, bool, list and More
7. 7
   Python Numbers: int, float, complex and Math Operations
8. 8
   Python Type Casting: int(), float() and str() Explained
9. 9
   Python Strings: Slicing, Methods and Escape Characters
10. 10
    Python String Formatting: f-strings and format() Examples
11. 11
    Python Booleans: True, False and Truthy Values
12. 12
    Python Operators: Arithmetic, Comparison, Logical and More

Collections

1. 13
   Python Lists: Create, Access, Add, Remove and Sort Items
2. 14
   Python Tuples: Immutable Sequences with Examples
3. 15
   Python Sets: Unique Items, Union and Intersection
4. 16
   Python Dictionaries: Key-Value Pairs with Examples

Control Flow and Functions

1. 17
   Python If…Else: Conditions, elif and Nested If
2. 18
   Python While Loops: break, continue and else
3. 19
   Python For Loops: range(), enumerate() and Nested Loops
4. 20
   Python Functions: def, Arguments, Return and *args
5. 21
   Python Lambda Functions: Syntax and Examples
6. 22
   Python Scope: Local, Global and nonlocal Variables
7. 23
   Python Try…Except: Handle Errors and Exceptions
8. 24
   Python User Input: input() and Validation

Modules and Files

1. 25
   Python Modules and pip: Import, Install and Virtual Environments
2. 26
   Python Dates: datetime, strftime and Date Arithmetic
3. 27
   Python Math Module: Functions, Constants and Rounding
4. 28
   Python JSON: Parse, Create and Save JSON Data
5. 29
   Python RegEx: re Module Patterns with Examples
6. 30
   Python File Handling: Open, Read, Write and Delete Files
7. 31
   Python CSV Files: Read and Write with the csv Module

Classes and the Web

1. 32
   Python Classes and Objects: __init__, self and Methods
2. 33
   Python Inheritance: Parent, Child Classes and super()
3. 34
   Python Iterators and Generators: iter(), next() and yield
4. 35
   Python Requests: Call REST APIs and Handle JSON Responses
5. 36
   Python Web Scraping with requests and BeautifulSoup

Data Analysis

1. 37
   Python NumPy Basics: Arrays, Indexing and Calculations
2. 38
   Python pandas Basics: DataFrames, Filtering and GroupBy
3. 39
   Python pandas: Read and Write Excel and CSV Files
4. 40
   Python Matplotlib: Line, Bar and Pie Charts Step by Step
5. 41
   Python in Excel: Use the PY Function for Data Analysis

Python with AI

1. 42
   Python with AI: Write Code with ChatGPT, Claude and Copilot
2. 43
   Call an AI API from Python: OpenAI and Anthropic Examples
3. 44
   Build a Chatbot in Python with an AI API Step by Step
4. 45
   Automate Excel Reports with Python and AI
5. 46
   Debug Python Code with AI: Read Errors and Fix Them Fast

Practice and Reference

1. 47
   Python Projects for Beginners: 10 Projects with Code
2. 48
   Python Cheat Sheet: Syntax Reference on One Page

Who this course is for

Excel and Google Sheets users who want to automate reports, analysts moving into pandas and dashboards, students preparing for data roles, and anyone who has tried to learn Python before and stalled. If you can write a spreadsheet formula, you can follow chapter 1.

How to practise

• Install Python locally with VS Code (chapter 2), or
• use a free browser editor such as online-python.com or Google Colab while you decide, and
• keep an AI assistant open in a second tab for the practice prompts.

Frequently asked questions