New NVIDIA DLI Workshop Offered in February

The University of Florida’s ambassadorship status with NVIDIA means that faculty, students, and staff have free training opportunities in accelerated computing and applied AI. Through the NVIDIA Deep Learning Institute (DLI) and in coordination with UFIT, a two-day Generative AI with Diffusion Models workshop is being offered for the first time at UF on February 22-23.

Day/Date/Time: Thursday and Friday, Feb. 22–23, from 12:00 – 4:00 p.m. each day

Location: Malachowsky Hall Auditorium – Room 1000

Register to Attend: Registration Link

The Generative AI with Diffusion Models workshop is taught by UF’s NVIDIA AI Technology Center Site Manager and Senior Data Scientist Kaleb Smith. Participants will gain a deeper understanding of denoising diffusion models to generate images from text prompts. Proficiency in PyTorch and deep learning models is required to attend, with participants who complete the 8-hour course earning a certificate of completion.

Learning highlights in this workshop include:

  • How to build a U-Net to generate images from pure noise
  • Improving the quality of generated images with the Denoising Diffusion process
  • Controlling the image output with context embeddings
  • Generating images from English text-prompts using CLIP

NVIDIA DLI workshops are in-person only and not recorded for later/repeat viewing. Anyone with questions about this workshop is welcome to contact Research Computing Training Team Lead Matt Gitzendanner.

NVIDIA Workshop for UF: Accelerating Data Science Flows

UFIT is hosting Accelerated Data Science with RAPIDS, a two-day workshop. The workshop, part of NVIDIA’s Deep Learning Institute (DLI), will be taught in two, four-hour sessions from 9:00 a.m. – 1:00 p.m. on November 15 and 17.

In Accelerated Data Science with RAPIDS, developers will learn to build and execute end-to-end GPU accelerated data science workflows to quickly explore, iterate, and get their work into production. Using the RAPIDS accelerated data science libraries, developers are able to apply a variety of GPU-accelerated machine learning algorithms, including XGBoost, cuGRAPH’s single-source shortest path, and cuML’s KNN, DBSCAN, and logistic regression to perform data analysis at scale. Workshop attendees get access to fully configured, GPU-accelerated servers in the cloud and guidance from a DLI-certified instructor. The workshop has a registration limit of 100, so registering early is strongly recommended. A $10 registration fee covers both sessions. Please contact Ms. Ying Zhang, AI team lead, with any questions about this workshop or other upcoming AI training and events.

The November 2021 AI and NVIDIA training schedule is listed below. Details and registration links are available on

Nov. 4: NVIDIA Metropolis
Nov. 9: AI in Matlab at RC
Nov. 15: NVIDIA DLI Workshop Accelerated Data Science with RAPIDS (part one)
Nov. 17: NVIDIA DLI Workshop Accelerated Data Science with RAPIDS (part two)
Nov. 30: NVIDIA CLARA Imaging