Introduction to Artificial Intelligence: Core Algorithms and Concepts

Artificial intelligence is transforming our world, yet the underlying algorithms often seem like a black box. Understanding how these systems actually make decisions, recognize speech, and generate text is the first step toward working confidently with modern technology. This text-based course guides you through the fundamental logic and mathematical structures of AI, taking you from a curious beginner to someone who understands the mechanics behind autonomous systems, recommendation engines, and generative models. What you'll learn: - Understand the core terminology and history of artificial intelligence and machine learning. - Explore classical search and optimization algorithms used in planning and decision-making. - Discover how supervised and unsupervised learning algorithms find patterns in raw data. - Learn the fundamentals of neural networks and deep learning architectures. - Grasp modern AI concepts including transformer models, vector databases, and prompt mechanics. - Evaluate the ethical considerations and limitations of algorithmic decision-making. We begin with essential foundational definitions and historical context before progressing through classic algorithmic approaches, neural networks, and modern generative AI concepts. Each chapter features clear, step-by-step written explanations and conceptual walkthroughs designed to build your intuition without requiring a background in advanced mathematics or programming. This course is created specifically for beginners who want a clear, conceptual understanding of AI technologies. Start reading today to demystify the algorithms shaping our digital future.