Spring 2025
INFO 290 Introduction to Large Language Models (LLMs) and Generative AI
This course on Generative AI blends the theoretical foundations of LLMs with hands-on applications. Topics include Transformer architectures, prompt engineering, API integration, and Retrieval Augmented Generation (RAG). The course emphasizes practical skills, including working with open-source models, fine-tuning LLMs, implementing graph-based enhancements and using Agentic technologies to build applications. Ethical considerations are integrated throughout, with a focused module on bias assessment and mitigation strategies. By the course's end, participants will possess a robust toolkit for leveraging LLMs for application development.
- Large Language Models (LLMs)
- Knowledge Graphs
- Generative AI to improve machine learning for painting attribution.
- Particle Swarm Optimization for Machine Learning
- The intersection of music and technology
Education:
- PhD (CS) SMU, 1992
- MS (CS) Georgia Tech, 1974
- MS (NeuroPsych) Emory Univ, 1972
- BS (Psychology) Fordham College, 1967
