Topics

Overview of class topics. Click on the titles for details.

Session 1: AI Foundations

Class Dates: Monday 2026-01-12, Wednesday 2026-01-14
The topics in this session include foundational elements of logic and its application in AI (specifically Horn clauses and SLD resolution), different knowledge representation schemes (production rules, frames, and literals), methods for generalization and learning within these schemes (LGG, attribute-only space search, heuristic learning, and knowledge acquisition), and approaches to handling uncertainty in expert systems. Examples from various problem domains, such as mass spectrometry, symbolic integration, chemistry, music analysis, and student modeling, illustrate the practical application of these concepts.
Read more →

Session 2: Generative AI & LLMs

Class Dates: Monday 2026-01-26, Wednesday 2026-01-21
This session provides a comprehensive overview of artificial intelligence (AI), focusing on the evolution, concepts, and applications of Generative AI. The session explores topics such as the history of AI, different types of machine learning, neural networks, deep learning, large language models, and AI agents. It examines various generative models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). The session emphasizes prompt engineering and transfer learning techniques for optimizing the performance of these models.
Read more →