AI Mastery

Learn, Build, and Earn with Artificial Intelligence: A Beginner-to-Expert Guide to AI Concepts, Tools, and Income Strategies

von Md Habibur Rahman

148 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Unlock the world of Artificial Intelligence and turn your knowledge into real skills, projects, and income with "AI Mastery: Learn, Build, and Earn with Artificial Intelligence". This beginner-to-expert guide takes you step by step-from understanding AI fundamentals to building your own AI tools and monetizing them effectively.Inside this book, you will discover: Part 1: Foundations of AI - Learn what AI is, its history, types, and how it's already transforming our daily lives. Explore ethical challenges, risks, and the critical concepts like machine learning, data, and algorithms, explained in simple, easy-to-understand language.Part 2: Core AI Skills and Tools - Master the essential skills to build AI solutions. Understand machine learning, deep learning, neural networks, and natural language processing. Get hands-on with tools and platforms like Python, TensorFlow, PyTorch, Google Colab, and AutoML services-no prior experience needed.Part 3: Earning with AI - Discover practical strategies to turn your AI knowledge into income. Learn freelancing with AI projects, creating and selling AI-powered digital products, designing high-converting prompts, launching your own AI-based service business, and generating passive income through newsletters and text templates. Step-by-step, actionable guidance ensures you can start earning-even with minimal investment.Whether you're a student, aspiring AI developer, freelancer, or entrepreneur, this book gives you the confidence and tools to learn AI, build projects, and earn money-all in one place.Start your AI journey today, master the technology of the future, and unlock new opportunities for skill, creativity, and income!

• Reihe: Independently published
• ISBN: 9798271886157
• Sprache: Englisch
• Erscheinungsdatum: 27.10.2025
• Größe: 216 x 140 mm
• Verlag: Independently published