Artificial Intelligence: Core Principles and Problem-Solving

Understanding how systems reason, learn, and solve complex problems is the key to mastering modern technology. This course demystifies the core computational methods behind artificial intelligence, taking you from foundational logic to modern machine learning concepts. Through clear written explanations and step-by-step conceptual walkthroughs, you will transition from a curious beginner to a confident thinker who understands how AI models represent knowledge and make decisions. What you'll learn: - Understand the core terminology, representations, and computational architectures of artificial intelligence. - Apply search strategies, including heuristic search and constraint propagation, to solve complex logic puzzles. - Analyze classical reasoning methods like rule chaining and formal logic to build rule-based systems. - Explore fundamental machine learning paradigms, including decision trees, support vector machines (SVMs), and neural networks. - Learn modern AI concepts such as prompt engineering basics and how vector databases support intelligent systems. - Practice evaluating AI models using standard performance metrics through structured written exercises. The curriculum begins with essential definitions and foundational search algorithms, guiding you systematically through logic-based reasoning before introducing classic and modern machine learning frameworks. This course is designed for absolute beginners, developers looking to understand the theory behind AI, or anyone curious about how intelligent systems work, with no prior programming or advanced mathematics experience required. Start reading today to build your foundational understanding of artificial intelligence.