, PAGE 01
TABLE OF CONTENTS
Chapter 1:
Understanding Artificial Intelligence (AI)
1.1 Definition & Core Concepts
1.2 History & Evolution of AI
1.3 Types of AI: Weak vs. Strong AI
Chapter 2:
The Foundation of Machine Learning (ML)
2.1 What is Machine Learning?
2.2 How Machine Learning Works: The Process
2.3 Key Terminologies in ML
Chapter 3:
Common Machine Learning Algorithms
3.1 Supervised Learning
3.2 Unsupervised Learning
3.3 Reinforcement Learning
Chapter 4:
Real-World Applications & Future Trends
4.1 AI in Daily Life
4.2 The Role of Neural Networks & Deep Learning
4.3 Ethical Considerations & Future Prospects
PAGE 02
TABLE OF CONTENTS
Chapter 1:
Understanding Artificial Intelligence (AI)
1.1 Definition & Core Concepts
1.2 History & Evolution of AI
1.3 Types of AI: Weak vs. Strong AI
Chapter 2:
The Foundation of Machine Learning (ML)
2.1 What is Machine Learning?
2.2 How Machine Learning Works: The Process
2.3 Key Terminologies in ML
Chapter 3:
Common Machine Learning Algorithms
3.1 Supervised Learning
3.2 Unsupervised Learning
3.3 Reinforcement Learning
Chapter 4:
Real-World Applications & Future Trends
4.1 AI in Daily Life
4.2 The Role of Neural Networks & Deep Learning
4.3 Ethical Considerations & Future Prospects
PAGE 02
