Introduction to Artificial Intelligence
Earn college credit with Introduction to Artificial Intelligence—a self-paced online course covering core AI concepts, search, basic machine learning ideas, and real-world applications with ethical considerations. Complete short lessons, quizzes, and assignments on your schedule, then finish with a proctored final exam. Ideal for CS electives and modern tech literacy, with transcript options.
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Upon the successful completion of this course, students will be able to: interpret key Artificial Intelligence (AI) concepts and history, describe the distinctions between AI types and models, and classify various AI systems in real-world contexts; analyze algorithms and intelligent agents, compute and interpret logarithmic functions and probability theories in AI, and evaluate data accuracy and precision; compare and contrast machine learning and AI, apply theoretical knowledge to develop AI-driven solutions, and implement AI programming languages like LISP and Prolog; design intelligent agents, evaluate decision-making models, and synthesize knowledge of Bayesian networks, neural networks, and decision trees to create AI solutions; and analyze AI's ethical implications, manage AI projects using advanced functionalities, and predict future AI technology directions and their societal impacts.
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Learning Outcomes
Upon the successful completion of this course, students will be able to: interpret key Artificial Intelligence (AI) concepts and history, describe the distinctions between AI types and models, and classify various AI systems in real-world contexts; analyze algorithms and intelligent agents, compute and interpret logarithmic functions and probability theories in AI, and evaluate data accuracy and precision; compare and contrast machine learning and AI, apply theoretical knowledge to develop AI-driven solutions, and implement AI programming languages like LISP and Prolog; design intelligent agents, evaluate decision-making models, and synthesize knowledge of Bayesian networks, neural networks, and decision trees to create AI solutions; and analyze AI's ethical implications, manage AI projects using advanced functionalities, and predict future AI technology directions and their societal impacts.
Major Course Topics
Major topics include essentials of Artificial Intelligence; Intelligent Agents; AI in search techniques; constraint satisfaction in AI; logical agents and advanced reasoning; machine learning and AI Reasoning; and the future of Artificial Intelligence.