Foundations of Applied AI. 3 credits

Catalog description

This course introduces the core principles and methodologies of Applied Artificial Intelligence (AI), focusing on the representation, reasoning, and learning techniques that power modern AI systems. Students will gain a foundational understanding of symbolic and statistical AI methods, including logic-based reasoning, search strategies, game theory, and decision-making models. Key topics include data and knowledge representation, machine learning, deep learning, natural language processing (NLP), intelligent agents, and automation. Students will explore data mining, information retrieval, speech and vision processing, large language models (LLMs), and human-in-the-loop AI systems. The course also covers mixed-initiative AI, bots, robotics, and AI-driven communication and reasoning. Beyond technical concepts, the course emphasizes ethical considerations, AI governance, and the societal impact of AI, covering bionics, neurotechnology, and responsible AI deployment. Offered by Info Sciences & Technology . May not be repeated for credit.