This introductory chapter lays the foundation for the course by exploring the historical development of Artificial Intelligence, its core concepts, and the key milestones that have shaped its evolution.

This chapter delves into the core of Artificial Intelligence: machine learning. Students will learn about various machine learning algorithms and their applications, as well as the process of data collection, feature engineering, model training, and performance evaluation.

In this chapter, students will explore the field of Natural Language Processing (NLP), which enables machines to understand, interpret, and generate human language.

Computer vision, the ability of machines to interpret and understand digital images and videos, is the focus of this chapter. Students will explore the core concepts and techniques of computer vision, including image preprocessing, object detection and recognition, semantic segmentation, and image classification.

In this chapter, students will delve into the decision-making and reasoning capabilities of AI systems. They will explore different approaches to decision-making and the role of knowledge representation, logical reasoning, and uncertainty management in AI-powered decision-making.

As Artificial Intelligence continues to permeate various aspects of our lives, it is crucial to understand the ethical and societal implications of these technologies. In this chapter, students will critically examine the ethical considerations surrounding AI, such as privacy, bias, transparency, and accountability.

In the final chapter of this course, students will delve into the future of Artificial Intelligence, exploring the emerging trends, cutting-edge advancements, and potential breakthroughs that could shape the years to come.