Chapter 1, Introduction to Generative AI, lets you discover the evolution of AI from traditional methods to generative AI, explore the foundation of LLMs, and understand how generative AI powers text, image, music, and video generation.

Chapter 2, OpenAI and ChatGPT: Beyond the Market Hype, dives into OpenAI’s ecosystem, explores the different model families (GPT-4, DALL·E, and Whisper), and understands ChatGPT’s rapid rise and its capabilities for everyday and professional use.

Chapter 3, Understanding Prompt Engineering, explores the art of crafting effective prompts, including techniques like ReAct and Chain of Thought (CoT), and shows how structured prompting enhances AI-generated responses.

Chapter 4, Boosting Day-to-Day Productivity with ChatGPT, leverages ChatGPT as a personal productivity assistant, showing how to automate tasks, improve writing, translate content, retrieve quick information, and enhance research efficiency.

Chapter 5, Developing the Future with ChatGPT, explores how ChatGPT aids developers in generating, optimizing, and debugging code and translating programming languages.

Chapter 6, Mastering Marketing with ChatGPT, uncovers how ChatGPT can revolutionize marketing—enhancing content creation, optimizing SEO, running A/B testing, and improving customer engagement with sentiment analysis.

Chapter 7, Research Reinvented with ChatGPT, shows how ChatGPT can assist researchers in brainstorming ideas, structuring studies, formatting bibliographies, and presenting findings in a clear and concise manner.

Chapter 8, Unleashing Creativity Visually with ChatGPT, explores ChatGPT’s multimodal capabilities, including GPT-4 Vision and DALL-E, enabling AI-driven image generation, visual Q&A, and enhanced creative workflows.

Chapter 9, Exploring GPTs, teaches the concept of GPTs, explores assistant-based AI workflows, and shows how to build your own AI-powered assistants for tasks like research, analysis, and marketing.

Chapter 10, Leveraging OpenAI Models for Enterprise-Scale Applications, delves into OpenAI’s model APIs, comprehends enterprise applications of LLMs, and explores how businesses can integrate generative AI into their workflows responsibly.

Chapter 11, Epilogue and Final Thoughts, reflects on the evolving landscape of generative AI, discusses ethical implications, and looks ahead to the future of AI.

The Appendix contains a set of hands-on examples of real-world use cases leveraging OpenAI and Python code.