Artificial Intelligence for Complete Beginners

Introduce the fundamentals of artificial intelligence, its history and applications, and illustrate how AI chatbots streamline recruitment on Facebook Messenger.

Trace the history of artificial intelligence from wartime code breaking and early learning systems to AI winters, Dartmouth 1956, Lisp, and Deep Blue.

Define artificial intelligence as a field creating intelligent machines that learn, reason, and plan, using machine learning (supervised and unsupervised), knowledge engineering, perception, computer vision, and robotics to tackle problems.

Explore how artificial intelligence spans health care, automotive, finance, government, video games, military, audit, advertising, and art, with concrete examples like dose optimization, driverless cars, and fraud detection.

Explore artificial intelligence and intelligent systems, showing how they reason, learn, store and retrieve memory, and adapt using linguistic, musical, logical-mathematical, spatial, bodily-kinesthetic, intrapersonal, and interpersonal intelligences.

Explore the scope of problems in artificial intelligence, including natural language understanding, automated reasoning, computer vision, machine translation, and common-sense knowledge, plus issues of brittleness and computational complexity.

Explore diverse artificial intelligence approaches, from symbolic and knowledge-based methods to sub symbolic, embodied, and Nouvelle AI. Trace the evolution through cybernetics, expert systems, neural networks, and soft computing.

Explore how intelligent search underpins reasoning, planning, and learning in artificial intelligence, from means and analysis and goal trees to configuration space, local searches, and neural networks.

Explore the seven artificial intelligence technologies—from reactive machines to artificial superhuman intelligence—and learn how biometric voice recognition and thumb impressions help prevent online fraud.

Explore agents and environments in artificial intelligence, including percepts, agent functions, and rational behavior; compare simple reflex, goal-based, and utility-based agents and the key environment properties.

Explore artificial intelligence expert systems that solve domain problems using a knowledge base, inference engine, and user interface, delivering advice, diagnoses, explanations, and predictions.

Explore artificial intelligence and robotics, where robots perceive, pick up, move, and affect the world to automate repetitive tasks, spanning power, locomotion, and actuators.

Differentiate strong AI, which mimics human cognition, from weak AI, a narrow task-focused system; the module portrays AI as a simulation, not a conscious mind.