Foundations of AI: Machine Learning, Generative AI, and Edge Computing

Artificial intelligence is transforming every industry, yet grasping how these technologies actually work can feel overwhelming. This course demystifies the core concepts of AI, machine learning, and modern hardware-efficient deployment. You will transition from a curious observer to a knowledgeable practitioner capable of discussing AI architectures, generative models, and deployment constraints with confidence. What you'll learn: - Understand the fundamental terminology, history, and core components of artificial intelligence. - Distinguish between supervised, unsupervised, and reinforcement learning paradigms. - Explore modern generative AI concepts, large language models, and basic prompt engineering. - Analyze how AI models run on hardware, including the basics of edge AI and resource-constrained computing. - Evaluate ethical considerations, bias, and security in modern AI deployments. This text-based course begins with essential definitions and foundational theories before guiding you through machine learning algorithms and practical hardware considerations. You will read clear explanations and review conceptual walk-throughs that solidify your understanding of modern intelligent systems. Designed entirely for beginners, this course requires no programming background or advanced mathematics experience. Start your journey into the world of artificial intelligence today.