Artificial Intelligence and Generative AI for Beginners by David M. Patel Summary

Artificial Intelligence & Generative AI for Beginners by David M. Patel is a practical guide introducing foundational AI concepts like machine learning, neural networks, and generative models. It provides step-by-step instructions for using tools like ChatGPT and MidJourney to enhance productivity, alongside real-world applications in business and personal projects.

This book is ideal for novices, professionals, and curious learners seeking to understand AI fundamentals without technical jargon. Entrepreneurs, creatives, and career-changers will benefit from its actionable advice on leveraging generative AI for innovation and efficiency.

Yes—readers praise its clear explanations of complex topics like backpropagation and large language models (LLMs), alongside hands-on guidance for AI tools. While some note minor editing issues, the book’s structured approach makes it a valuable primer for AI newcomers.

Patel breaks down machine learning, neural networks, LLMs, and generative AI workflows. He emphasizes practical applications, such as optimizing ChatGPT prompts and creating AI-generated visuals with MidJourney, while explaining foundational math and algorithms.

Yes. Patel dedicates sections to mastering ChatGPT for text generation and MidJourney for image creation, providing templates and strategies for effective prompt engineering. These tools are framed as essential for boosting creative output and business scalability.

David M. Patel holds an M.S. in Computer Science and has 15+ years as an AI consultant. His expertise spans healthcare, finance, and tech industries, making him a trusted voice for translating technical AI concepts into accessible advice.

The book bridges theory and practice, teaching readers to apply generative AI for tasks like data analysis, content creation, and problem-solving. Patel highlights AI’s role in future-proofing careers across industries, from marketing to software development.

Some reviewers note occasional typos and oversimplified explanations, likely due to its rapid publication. However, these do not detract from its value as an introductory resource.

Unlike overly technical textbooks, Patel’s guide prioritizes actionable insights over theory. It stands out for its focus on generative AI tools and real-world use cases, making it more practical for non-technical readers than academic references.

As generative AI reshapes industries, Patel’s strategies for ethical AI use, prompt engineering, and leveraging LLMs align with current needs in automation, creative workflows, and data-driven decision-making.

Patel emphasizes, “You are not going to be replaced by AI, you are going to be replaced by a human using AI”—a rallying call for readers to adopt AI tools proactively. He also outlines frameworks for iterative AI experimentation and risk assessment.

Absolutely. Patel provides templates for automating customer service, generating marketing content, and optimizing workflows using generative AI. Case studies illustrate cost savings and scalability for startups and SMEs.