# Introduction to AI

Overview of artificial intelligence concepts and applications.

# AI History {.sub}

Key milestones in the development of AI technologies.

# AI Applications {.sub}

Real-world use cases, including healthcare, finance, and automation.

# AI Ethics {.sub}

Considerations for responsible AI development and deployment.

# Machine Learning Basics

Introduction to machine learning models and techniques.

# Supervised Learning {.sub}

Concepts of labeled data and predictive modeling.

# Unsupervised Learning {.sub}

Techniques for clustering and pattern discovery.

# Conclusion

Summary of AI's impact and future directions.