Data Science and Machine Learning, is designed to serve as a comprehensive starting point for students, professionals, and enthusiasts who are new to the ?eld. It provides a well-rounded foundation in both the theoretical concepts and practical applications of data science and machine learning, blending statistical thinking, computational tech-niques, and domain knowledge. The book covers essential topics including data preprocessing, exploratory data analysis, supervised and unsupervised learning, model evaluation, and the ethical considerations of AI. Programming examples and exercises are included throughout, primarily using Python and its widely adopted librar-ies such as Pandas, NumPy, Scikit-learn, and Matplotlib. What sets this book apart is its approachable and structured learning path.Beginning with fundamental concepts, it gradually introduces more com-plex ideas, ensuring that readers develop both intuition and practical skills.Whether you are a student starting your journey, a professional looking to transition into data science, or an educator seeking to introduce the subject,this book aims to make the learning process engaging, insightful, and applicable
