Fundamental of AI - Fundamental of AI for GTU 24 Course (II- COMMON - BE02000041)  (Paperback, Anamitra Deshmukh-Nimbalkar, Dr. Ajay N. Upadhyaya)

Syllabus Fundamental of AI - (BE02000041) Total Credits L + T + (PR/2) Assessment Pattern and Marks Total Marks C Theory Tutorial / Practical ESE (E) PA / CA (M) PA / CA (I) ESE (V) 02 70 30 - - 100 Unit No. Content 1. Introduction : • History & overview of Artificial Intelligence. • Definition of Artificial Intelligence. • Artificial Narrow Intelligence, Artificial General Intelligence, Artificial Super Intelligence. • Concepts of Production, Agents and Environments. • Characteristics of Intelligent Agents, Concept of Rationality, Nature of Environments. (Chapter - 1) 2. Knowledge Representation : • Concept of Knowledge representation. • Introduction to Natural Language processing. • Concept of Pattern recognition. • Introduction to Expert systems. (Chapter - 2) 3. Basics of Machine Learning : • Learning from examples. • Forms of Learning - Supervised learning, Unsupervised learning, Reinforcement learning • Simple Models - Linear regression, Logistic regression, Support Vector Machines (SVM) etc. (Chapter - 3) 4. Deep Learning : • Concept of Deep Learning. • Introduction to Neural Networks. • Types of Deep Learning models. • Deep learning applications. (Chapter - 4) 5. Modern Artificial Intelligence : • Large Language Models (LLMs). • Use-cases : ChatGPT, Gemini, Bhashini, Krutrim etc. • Current Issues & Future Challenges of AI. (Chapter - 5)