Artificial Intelligence for Class X

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.

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

Dr. Harsh Bhasin is a researcher and academic specializing in deep learning, algorithms, and medical imaging, with over a decade of experience in computational mental health. He is currently associated with Bennett University, India, and previously served as a deep learning consultant and faculty member at institutions including Jamia Hamdard and Delhi Technological University (DTU).

He earned his Ph.D. from Jawaharlal Nehru University, New Delhi, under the prestigious Visvesvaraya
Fellowship (Ministry of Electronics and Information Technology, Government of India). His doctoral work focused on machine learning–based diagnosis and conversion prediction of Mild Cognitive Impairment. He has also contributed to a government-funded collaborative project on depression diagnosis involving SIPL and Ram Manohar Lohia Hospital, advancing data-driven neuropsychiatric assessment.

Dr. Bhasin has authored books published by Oxford University Press and APress, and his research has appeared in leading international journals and conferences, including Alzheimer’s & Dementia, Soft Computing, and BMC Medical Informatics & Decision Making. His current research focuses on EEG-based diagnostics, cognitive impairment conversion prediction, and translational machine learning for depression diagnosis.


Dr. Vishal Deshwal is a senior data scientist with over 5 years of experience building production machine
learning, NLP, LLM, analytics, and workflow automation solutions. He is deeply passionate about explaining complex technologies and making them accessible to the next generation of learners. Throughout his career developing solutions across the education, environmental risk, and healthcare sectors, he has remained dedicated to bridging the gap between advanced technological concepts and foundational learning.

He earned his Ph.D. in deep learning and neural architecture from Western Sydney University, where he also completed his master of data science. As a researcher, Dr. Deshwal has made extensive technical contributions, including engineering a Vision Transformer wildfire forecasting pipeline and developing the novel Layer-wise Adaptive Sine Activation (LASA) function. Furthermore, his academic research has been featured in multiple peer-reviewed publications and presented at leading events such as the Alzheimer's Association International Conference (AAIC).

Dr. Deshwal strongly believes in the transformative power of artificial intelligence and strives to empower K-12 students with the tools they need to safely navigate and shape an AI-driven world.