Event box

Date:
Tuesday, March 3, 2026
Time:
1:00pm - 4:00pm
Space:
Fondren Library 109
Hosted by:
OIT Research and Data Science Services

Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate, faster diagnoses in patients. Retail businesses use it to offer personalized customer shopping experiences. Automakers use it to make personal vehicles, shared mobility, and delivery services safer and more efficient. Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software

During the workshop, students will:

  • Learn the fundamental techniques and tools required to train a deep learning model
  • Gain experience with common deep learning data types and model architectures
  • Enhance datasets through data augmentation to improve model accuracy
  • Leverage transfer learning between models to achieve efficient results with less data and computation
  • Build confidence to take on your own project with a modern deep learning framework

Students will have opportunity to get certificate for this workshop from NVIDIA up on finishing the final exam in class

More information: https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-FX-01+V3

For online students, you can attend via Zoom link: https://smu.zoom.us/j/8918870467?omn=97632707066

Before coming to the workshop, please create an account for NVIDIA DLI here using your smu account: 
https://learn.nvidia.com/dli-event

Presented by Tue Vu

Registration has closed.

Any person who requires a reasonable accommodation on the basis of a disability in order to participate in this program should contact Dr. Tue Vu (tuev@smu.edu) at least one week prior to the event to arrange for the accommodation. 
 

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