Full course description
Course Overview
Join Professor KZ Zhang for a deep dive into the technical framework behind the large language model (LLM), including solutions for developing, training, and implementing a model on a custom data set. The solution can be implemented in any environment, even without extensive computing resources.
Who should take this course?
This course is intended for anyone ready to move past the theoretical and into the hands-on techniques of building and training an LLM. It is especially useful for practitioners in industries with restrictive data privacy rules, such as government, federal contracting, or healthcare. Participants should be familiar with Python and linear algebra (e.g. matrix multiplication). Participants will be asked to apply lessons learned in real-time coding exercises, so a (free) Google Colab account is needed.
Why Build Your Own Model?
Industry-Specific Accuracy: Develop AI models that understand complex terminology and regulations unique to your industry, ensuring precise and reliable results.
Data Security & Compliance: Keep sensitive information confidential and compliant by training models on internal data.
Operational Efficiency: Streamline processes and enhance decision-making with custom AI solutions designed for the specific needs of your environment.
Valuable Outcomes
Define the foundations of LLMs/transformers.
Apply a pre-trained and fine-tuned paradigm in text understanding.
Deploy a customized LLM for your organization.
Course Dates
Day 1: Friday, August 1, 2025, 9:00 AM - 2:30PM
Day 2: Friday, August 8, 2025, 9:00 AM - 2:30PM
Day 3: Friday, August 15, 2025, 9:00 AM - 2:30PM
Day 4: Friday, August 22, 2025 9:00 AM - 2:30 PM
Weekly Schedule
Week 1: Introduction to foundation models, prompting fundamentals
Week 2: Explore text similarity with Embeddings, introduction to RAG, building a RAG Q&A system
Week 3: AI agent components, development of AI agents, agents companion, building an agentic system in LangGraph
Week 4: Fine-tuning LLMs, adding real-world data to a model
Info Sessions:
Date TBD
Attend an info session to ask questions and get more information about how this workshop can help your organization leverage generative AI tools.
Location:
Van Munching Hall, University of Maryland College Park Campus. Room TBD.
Address: 7621 Mowatt Ln, College Park MD 20742
Daily Agenda
9:00 AM Workshop begins
12:00 PM Lunch break
1:00 PM Workshop resumes
2:30 PM End of day
Cancellation and Refund Policy
Cancellation requests must be submitted in writing at least seven days before the program start date to receive a full refund. No refunds are provided within seven days of the program start date, but participants may defer their enrollment to another session of the same program offered later.
Smith Executive Education Homepage | Download Brochure | Contact us: rhsmith-execed@umd.edu