"Artificial Intelligence as a subject has grabbed a lot of attention after getting a place in the All India Council for Technical Education's (AICTE) list of emerging areas. It was included as an elective/core subject in the undergraduate curriculum of the computer science program by many universities. AI is evolving as a subject and now many colleges are offering separate undergraduate programs in AI. In most universities, the AI course is made up of AI algorithms, machine learning and deep learning. This book is written for readers interested in the algorithms and their usage involved in Artificial Intelligence (AI). There are several aspects important in the study of AI like natural language understanding, knowledge representation, machine learning, image processing, pattern recognition and so on. However the text focusses categorically on cognitive computing, including the areas like knowledge representation, reasoning, and search. It focuses on theoretical analysis of search algorithms, and their implementation and will be useful for both undergraduate and graduate courses offering a degree in AI or where AI is taught as a paper with a focus on search algorithms. The coverage has evolved around the syllabus of the courses like probability and statistics, theory of probability, statistics and so on. The learners taking this course usually struggle with the mathematical concepts and applications of theoretical concepts. The author has tried to bridge this gap with the case-based approach and computer-oriented projects. The MATLAB/Python based exercises and the case study projects in the book will also provide hands-on experience to the students. The author has earnestly made an attempt at creating a path for experiential learning through his book, which is a key takeaway from the Indian New Education Policy, 2020"--