Introduction to AI and its Applications 1BAIA103
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Browse ResourcesSyllabus Overview
Module 1: Introduction to Artificial Intelligence
Artificial Intelligence, How Does AI Work?, Advantages and Disadvantages of Artificial Intelligence, History of Artificial Intelligence, Types of Artificial Intelligence, Weak AI, Strong AI, Reactive Machines, Limited Memory, Theory of Mind, Self -Awareness, Is Artificial Intelligence Same as Augmented Intelligence and Cognitive Computing, Machine Learning and Deep Learning. Machine Intelligence: Defining Intelligence, Components of Intelligence, Differences Between Human and Machine Intelligence, Agent and Environment, Search, Uninformed Search Algorithms, Informed Search Algorithms: Pure Heuristic Search, Best-First Search Algorithm (Greedy Search). Knowledge Representation: Introduction, Knowledge Representation, Knowledge -Based Agent, Types of Knowledge. Textbook 1: Chapter 1 (1.1-1.5), Chapter 3 (3.1-3.7.2), Chapter 4 (4.1-4.4)
Module 2: Detailed Syllabus
Introduction to Prompt Engineering , Introduction to Prompt Engineering, The Evolution of Prompt Engineering, Types of Prompts, How Does Prompt Engineering Work?, Comprehending Prompt Engineering's Function in Communication, The Advantages of Prompt Engineering, The Future of LLM Communication. Prompt Engineering Techniques for ChatGPT , Introduction to Prompt Engineering Techniques, Instructions Prompt Technique, Zero, One, and Few Shot Prompting, Self-Consistency Prompt. Prompts for Creative Thinking: Introduction, Unlocking Imagination and Innovation. Prompts for Effective Writing: Introduction, Igniting the Writing Process with Prompts. Textbook 2: Chapters 1, 3, 4 & 5
Module 3: Machine Learning
Techniques in AI, Machine Learning Model, Regression Analysis in Machine Learning, Classification Techniques, Clustering Techniques, Naïve Bayes Classification, Neural Network, Support Vector Machine (SVM). Textbook 1: Chapter 2 (2.1-2.8)
Module 4: Trends in AI
AI and Ethical Concerns, AI as a Service (AIaaS), Recent trends in AI, Expert System, Internet of Things, Artificial Intelligence of Things (AIoT). Textbook 1: Chapter 8 (8.1, 8.2, 8.4), Chapter 9 (9.1- 9.3)
Module 5: Detailed Syllabus
Robotics, Robotics-an Application of AI, Drones Using AI, No Code AI, Low Code AI. Textbook 1: Chapter 8 (8.3), Chapter 1 (1.7, 1.8, 1.10, 1.11) Industrial Applications of AI: Application of AI in Healthcare, Application of AI in Finance, Application of AI in Retail, Application of AI in Agriculture, Application of AI in Education, Application of AI in Transportation, AI in Experimentation and Multi-disciplinary research. Textbook 3: Chapter 3, Chapter 5 (5.1)
Textbooks & Resources
- Reema Thareja, Artificial Intelligence: Beyond Classical AI, Pearson Education, 2023.
- Ajantha Devi Vairamani and Anand Nayyar, Prompt Engineering: Empowering Communication , 1st Edition, CRC Press, Taylor & Francis Group, 2024. (DOI: https://doi.org/10.1201/92319).
- Saptarsi Goswami, Amit Kumar Das and Amlan Chakrabarti, “AI for Everyone – A Beginner’s Handbook for Artificial Intelligence”, Pearson, 2024.
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What is 1BAIA103 (Introduction to AI and its Applications)?
Introduction to AI and its Applications (1BAIA103) is a VTU course covered through module-wise syllabus, notes, and PYQ-driven exam practice available on this page.
How many credits is 1BAIA103?
Credits for 1BAIA103: 04.
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