Course Overview
Artificial Intelligence Foundations introduces students to the theoretical structure of intelligent systems, search, optimization, machine learning, neural networks, symbolic reasoning, and AI system design. Learners study the foundational ideas that support modern AI tools while distinguishing conceptual understanding from tool usage.
Artificial Intelligence Foundations Topics
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Search and State Spaces
Focused study of search and state spaces as a core topic within artificial intelligence foundations, emphasizing conceptual understanding, technical vocabulary, reasoning patterns, and links to practical computing systems.
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Optimization
Focused study of optimization as a core topic within artificial intelligence foundations, emphasizing conceptual understanding, technical vocabulary, reasoning patterns, and links to practical computing systems.
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Machine Learning Concepts
Focused study of machine learning concepts as a core topic within artificial intelligence foundations, emphasizing conceptual understanding, technical vocabulary, reasoning patterns, and links to practical computing systems.
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Neural Network Foundations
Focused study of neural network foundations as a core topic within artificial intelligence foundations, emphasizing conceptual understanding, technical vocabulary, reasoning patterns, and links to practical computing systems.
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Symbolic AI
Focused study of symbolic ai as a core topic within artificial intelligence foundations, emphasizing conceptual understanding, technical vocabulary, reasoning patterns, and links to practical computing systems.
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AI Systems Theory
Focused study of ai systems theory as a core topic within artificial intelligence foundations, emphasizing conceptual understanding, technical vocabulary, reasoning patterns, and links to practical computing systems.