CONTENTS:
Preface
1. Introduction to AI and Machine Learning 1
1.1 What is Artificial Intelligence (AI)
1.2 Why Learn AI Early?
1.3 Examples of AI in Everyday Life
1.4 The AI Project Cycle
1.5 Ethics in AI
2. AI Applications and Methodologies 14
2.1 AI Applications (Where AI is used?) 14
2.2 How AI Works (Methodologies: ML, DL, NLP, etc.)
2.3 AI for Sustainable Development Goals (SDGs)
3. Mathematical Foundations for AI (Basic) 25
3.1 Structured vs. Unstructured Data
3.2 Basic Statistics: The AI’s Summary Tool (Mean, Median, Mode)
3.3 Introduction to Graphs and Charts: Drawing Stories with Data
4. Introduction to Algorithm and Python Programming
4.1 Understanding Algorithm
4.2 Designing Simple Algoritm
4.3 Introduction to Python Programming
4.4 Python Syntax and Indentation
4.5 Python Variabes and Data Types
4.6 Python Operators
4.7 Python Collections: Lists, Tuples, Sets, Dictionaries
4.8 Python if-else, Loops
4.9 Python Libraries 69
4.10 Working with Pandas: Introduction
5. Hands on Practical AI Tools 81
5.1 ChatGPT Tutorial
5.2 Best AI Presentation Maker & Website Builder
5.3 Image Generation AI tools
5.3.1 VHEER.AI 
5.3.2 Ideogram 
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