NVIDIA WEBINAR
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The call for data science and machine learning skills is soaring and classrooms are on the frontlines of feeding the demand. NVIDIA Teaching Kits lower the barrier of incorporating AI and GPU computing in coursework. Listen to NVIDIA’s higher education leadership and academic partners discuss opportunities for online training, certification, and cloud access to GPUs for teachers and students.
By attending this webinar, you'll learn:
- Access Teaching Kits with curriculum materials.
- Gain free online training, certification and cloud access to GPUs for teachers and students.
- Hear real examples of leading academics using these materials in the classroom.
ON-DEMAND WEBINAR REGISTRATION
THANK YOU FOR REGISTERING FOR THE WEBINAR
You will receive an email with instructions on how to join the webinar shortly.Main Content
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DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speaker
Joe Bungo
Deep Learning Institute (DLI) Program Manager, NVIDIAJoe Bungo is the Deep Learning Institute (DLI) Program Manager at NVIDIA where he enables the use of deep learning and GPU accelerated computing technologies in universities, including curriculum and teaching material development, DLI University Ambassador/Instructor Certification, facilitation of academic ecosystems, and hands-on workshops. Previously, he managed university programs at ARM Inc. and worked as an applications engineer. Joe received his degree in Computer Science from the University of Texas at Austin.
Sunita Chandrasekaran
Assistant Professor, University of DelawareSunita Chandrasekaran is currently an Assistant Professor at the University of Delaware (UDEL), USA. Her research interests span exploring high-level programming models, language features, migrating scientific applications to supercomputers, compiler and runtime systems. She was a postdoctoral research fellow at the University of Houston prior to joining UDEL. She holds a PhD degree from NTU, Singapore and, a Bachelors in Engineering from Anna University, India. She was a recipient of the 2016 IEEE CS TCHPC Award for Excellence for Early Career Researchers.
Zoran Kostic
Associate Professor, Columbia UniversityZoran Kostic completed his Ph.D. in Electrical Engineering at the University of Rochester and his Dipl. Ing. degree at the University of Novi Sad. His present research addresses Internet of Things systems and physical data analytics, smart cities, and applications of deep learning in autonomous vehicle navigation, medicine and health. His work comprises a mix of research, system architecture and software/hardware development, which resulted in a notable publication record, three dozen patents, and critical contributions to successful products.
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