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Quantic School of Business and Technology
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Our courses are approved by the American Council on Education (ACE) — the same body that approves AP and IB — and are accepted for credit by thousands of universities, including yours.

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Learning Outcomes
Quantic School of Business and Technology
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.
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