Introduction to Artificial Intelligence and Core Algorithms

Artificial Intelligence is reshaping how we solve complex problems, make decisions, and automate tasks. To truly understand this field, you must look beyond the hype and master the foundational algorithms and logic that power intelligent systems. This course offers a clear, structured path to understanding both classic and modern AI techniques without requiring prior specialized knowledge. You will transition from a curious beginner to a practitioner who understands how AI systems reason, search for solutions, and learn from data. Through step-by-step written explanations and pseudocode, you will grasp the core mechanics of state-space search, knowledge representation, and basic machine learning. What you'll learn: - Understand the core definitions, history, and philosophical foundations of AI - Master classic search algorithms including depth-first, breadth-first, and heuristic-based A* search - Apply propositional and first-order logic to represent knowledge and solve reasoning problems - Explore modern machine learning fundamentals, including supervised learning and neural network basics - Understand the concept of prompt engineering and how large language models function at a high level - Evaluate ethical considerations, bias, and responsible AI practices in modern systems We begin with essential terminology and the historical context of intelligent agents. From there, you will progress through systematic search methodologies, knowledge representation, and transition into modern data-driven AI approaches and neural network architectures. This course is designed for absolute beginners, software developers looking to pivot into AI, and students seeking a structured conceptual framework. No prior background in advanced mathematics or machine learning is required. Start reading today to build a strong, permanent foundation in the principles of artificial intelligence.