Fundamentals of Machine Learning and Deep Learning for Product Builders

Artificial intelligence is transforming how we build software, yet understanding how these systems actually work can feel overwhelming. This text-based course demystifies the core concepts of modern AI, helping you bridge the gap between technical complexity and practical application. You will transition from a curious observer to a knowledgeable practitioner capable of discussing, evaluating, and planning AI-driven solutions. What you'll learn: - Understand foundational machine learning algorithms, training workflows, and evaluation metrics - Explore deep learning architectures, neural networks, and how deep layers extract complex features - Apply basic prompt engineering concepts and understand retrieval-augmented generation patterns - Evaluate ethical considerations, including bias mitigation, fairness, and data privacy in AI systems - Master key terminology to collaborate effectively with data scientists and engineering teams Starting with fundamental definitions and essential terminology, you will progress through the mechanics of training models, structuring neural networks, and addressing contemporary challenges like bias and model drift. This comprehensive guide ensures you understand both the capabilities and the limitations of modern AI. This course is designed for beginners, product managers, designers, and business professionals who want to understand AI technologies from the ground up without needing a background in advanced mathematics or programming. Step into the world of intelligent systems and start making informed AI decisions today.