Large Language Model Training and Development

Course Overview
Join Professor KZ Zhang for a deep dive into the technical framework behind the large language model (LLM), including solutions for developing and training 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?
While this course is intended for anyone interested in how an LLM works, it is especially useful for 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.

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, July 25, 2025, 9:00 AM - 2:30PM
Day 2: Friday, August 1, 2025, 9:00 AM - 2:30PM
Day 3: Friday, August 8, 2025, 9:00 AM - 2:30PM
Day 4: Friday, August 15, 2025, 9:00 AM - 2:30PM

Lunch is provided for participants.

Info Sessions:
Thursday, June 27 1:00 - 1:30 PM (Click here to register)

Attend an info session to ask questions and get more information about how this workshop can help your organization leverage generative AI tools.

Daily Agenda
9:00 AM Workshop begins
12:00 PM Lunch break (Boxed lunch provided)
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