Description Artificial intelligence is reshaping how we live, work, learn, and solve complex problems. For students entering a technology-driven world, understanding the fundamentals of AI is an increasingly valuable skill. This comprehensive guide introduces machine learning, data science, computer vision, and natural language processing in a clear and engaging way for Class X students. Designed to build both conceptual knowledge and practical skills, the book provides a structured journey through the AI landscape. It covers topics ranging from decision trees to neural networks and introduces the key stages of AI project development, including problem scoping, data acquisition, data exploration, modelling, and evaluation. It also develops important career-readiness skills and introduces responsible AI, ethical practices, and green computing. By the end of this book, readers will understand fundamental AI concepts and gain confidence in using Python and modern AI tools. Students will be equipped to move from passive users of technology to active creators who can explore ideas and develop their own AI projects. Whether you are a student, educator, or technology enthusiast, this book provides an accessible foundation for learning and creating in an AI-enabled world. What you will learn Understand the fundamentals of machine learning, deep learning, computer vision, and natural language processing. Apply problem scoping, data acquisition, data exploration, modelling, and evaluation. Develop practical Python programming skills using modern AI libraries. Explore neural network structures, learning processes, and real-world applications. Build communication, self-management, ICT, and entrepreneurial skills. Examine responsible AI practices, ethical considerations, and sustainable computing. Who this book is for This book is designed primarily for CBSE Class X students, educators, and anyone curious about artificial intelligence. It offers a clear and accessible introduction to the field and does not require extensive prior technical knowledge. Table of Contents 1. Communication Skills 2. Self-management 3. Information and Communication Technology Skills 4. Entrepreneurial Skills 5. Green Skills 6. Introduction to Artificial Intelligence 7. Artificial Intelligence Life Cycle 8. Python Fundamentals 9. Advanced Python Functions 10. Statistical Data and No Code AI for Statistical Data 11. Data Science 12. Computer Vision 13. Natural Language Processing 14. Evaluation 15. Ethics in Artificial Intelligence
