Ready to dive into the world of artificial intelligence-but not sure where to start? This beginner-friendly guide gives you the tools, confidence, and clear step-by-step strategies to build real-world AI systems from scratch-no PhD required. Whether you're a curious learner, career changer, or aspiring developer, AI Engineering for Beginners walks you through the essentials of machine learning, neural networks, data pipelines, model deployment, and responsible AI practices. You'll build your first models, learn the tools professionals use, and gain the skills to pursue a career in one of the most exciting fields in tech. Inside this book, you'll learn:What AI engineering is-and how it's different from research or data science How machine learning works (including supervised, unsupervised, and reinforcement learning) How to collect, clean, and prepare real-world data How to build, train, and evaluate your own AI models How to deploy models using tools like Docker, FastAPI, and cloud platforms How to think critically about AI ethics, bias, and transparency What jobs exist in AI-and how to build a portfolio that gets you hired Written in a friendly, accessible style inspired by bestselling educators, this book turns intimidating concepts into understandable, actionable knowledge. Whether you're just curious or ready to start building, AI Engineering for Beginners is your launchpad into the future of intelligent systems.
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