Artificial intelligence (AI) is a fundamental part of our daily lives, transforming industries, reshaping jobs, and redefining how we interact with technology. From the personalized recommendations on our phones to the intricate systems that power autonomous vehicles, AI is the invisible force driving innovation. This book seeks to demystify this powerful field for undergraduate students. It is a clear, accessible, and comprehensive guide that not only covers the theoretical underpinnings of AI but also connects them to real-world applications. The book reflects the latest advancements, including the rise of Generative AI and the critical skill of Prompt Engineering.
Whether you are a student, a teacher, a manager, an entrepreneur, or a social innovator, this book will help you develop your creative confidence and competence and enable you to create positive change in the world.
Salient features
About the Author Preface Acknowledgements Chapter 1: Introduction to Artificial Intelligence 1.1 What is Artificial Intelligence? 1.2 Scope of AI 1.3 Historical Evolution of AI 1.4 Influential Figures and Institutions in AI History 1.5 Differentiating Between AI and Human Intelligence 1.6 Artificial General Intelligence and Industry Applications 1.7 Key Milestones in AI Research 1.8 Inter-disciplinary Problem Solving Summary Exercises Answers Chapter 2: AI Subfields and Their Core Technologies 2.1 Overview 2.2 Knowledge Engineering 2.3 AI Subfields Summary Exercises Answers Chapter 3: Applications of AI 3.1 Introduction 3.2 Healthcare 3.3 Finance 3.4 Education 3.5 Agriculture 3.6 Transportation 3.7 Customer Service and Retail Summary Exercises Answers Chapter 4: Ethics, Bias, and Social Implications 4.1 Introduction 4.2 Bias in AI 4.3 Fairness in AI Decision-making 4.4 Transparency in AI Systems 4.5 Accountability in AI 4.6 Data Privacy and Security Concerns 4.7 AI Employment and Workforce Transformation 4.8 Inclusivity, Sustainability, and Reliability in AI Systems 4.9 AI and Social Inequality Summary Exercises Answers Chapter 5: Generative AI and Its Applications 5.1 Introduction 5.2 How It Works 5.3 ChatGPT 5.4 Gemini: Google’s Multimodal Gen AI 5.5 Hugging Face 5.6 Perplexity 5.7 Gen AI and Creativity 5.8 Gen AI-powered Slide Generation Tools 5.9 Gen AI in Research and Innovation 5.10 Gen AI in Education 5.11 Gen AI in Business 5.12 Gen AI in Healthcare 5.13 Gen AI in Entertainment 5.14 Future Trends in Generative AI Summary Exercises Answers Chapter 6: Prompt Engineering and Its Applications 6.1 Introduction 6.2 Definition and Importance of Prompt Engineering 6.3 Techniques for Effective Prompting 6.4 Role of Prompts in AI/ML Interaction 6.5 Challenges in Prompt Engineering 6.6 Future Scope in Human–AI Collaboration 6.7 Case Studies and Real-World Applications 6.8 Summarization and Simplification 6.9 Creative Content Generation 6.10 Storytelling and Fiction 6.11 Question-Answering and Chatbots: Customer Service 6.12 Student Help and Tutoring 6.13 Domain-specific Applications: Education 6.14 Domain-specific Applications: Healthcare 6.15 Domain-specific Applications: Business Summary Exercises Answers Chapter 7: Practical Session: Laboratory Work 7.1 Introduction 7.2 Creating Mind Maps with Canva 7.3 Exploring Napkin AI for Concept Mapping 7.4 Text Analysis Using NLP Tools 7.5 Building an Image Classifier 7.6 Simulating AI Chatbots in Education 7.7 ChatGPT for Text Generation 7.8 Hugging Face for Model Deployment 7.9 DALL·E for Image and Video Generation 7.10 Observing Bias in Generative Models 7.11 Practising Prompt Engineering 7.12 Creative Writing with Prompts 7.13 Content Generation Strategies 7.14 Using SlidesGPT for Slide Generation 7.15 Designing Digital Content with AI 7.16 Branding and Visual Identity with AI Summary
Appendix: Model Question Papers Index