AI Study Series Part 1: Foundations of Artificial Intelligence

Welcome to Part 1 of the University AI Study Series. This section will help you build a strong foundation in Artificial Intelligence. Whether you’re a curious beginner or a future AI engineer, these core concepts are the first steps in understanding how intelligent machines are built and taught to reason.

What is Artificial Intelligence?

AI is the science of creating machines that can perform tasks that typically require human intelligence—like understanding language, recognizing patterns, solving problems, and making decisions. These systems rely on concepts from logic, probability, learning, and decision theory.

This part introduces you to intelligent agents, search algorithms, problem solving, and knowledge representation — essential building blocks of AI.

Core Topics Covered

• Search Algorithms & Game Trees (e.g., A*, Minimax)
• Logic & Reasoning (Propositional and First-Order Logic)
• Probability, Bayes Networks, and Decision Making
• Intelligent Agents and Rational Behavior

Start Learning from Reputable Courses

• CS50's Introduction to AI with Python – Harvard: An ideal hands-on introduction to AI concepts using Python, designed for beginners.
• MIT 6.034: Artificial Intelligence: A free, in-depth MIT course covering knowledge representation, reasoning, learning, and perception.
• Stanford CS221: Learn how machines use principles and techniques to perform intelligent actions.

Why This Foundation Matters

Understanding these basics helps you interpret how AI systems are structured and function. These skills will later support your understanding of machine learning, neural networks, and AI ethics.

Once you're confident with the foundational topics, move on to Part 2: Machine Learning Essentials, where you'll learn how machines learn from data and improve over time.