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GTC ON-DEMAND

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Abstract:
The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems. Developers, data scientists, researchers, and students can get practical experience powered by GPUs in the cloud and earn a certificate of competency to support professional growth. DLI offers self-paced, online training for individuals, instructor-led workshops for teams, and downloadable course materials for university educators. The DLI University Ambassador Program enables qualified educators to teach DLI workshops at university campuses and academic conferences to faculty, students, and researchers at no cost, complementing the traditional theoretical approaches to university education in machine learning, data science, AI, and parallel computing.
The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems. Developers, data scientists, researchers, and students can get practical experience powered by GPUs in the cloud and earn a certificate of competency to support professional growth. DLI offers self-paced, online training for individuals, instructor-led workshops for teams, and downloadable course materials for university educators. The DLI University Ambassador Program enables qualified educators to teach DLI workshops at university campuses and academic conferences to faculty, students, and researchers at no cost, complementing the traditional theoretical approaches to university education in machine learning, data science, AI, and parallel computing.  Back
 
Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2019
Session ID:
SC1903
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Abstract:

The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems across autonomous vehicles, digital content creation, healthcare, finance, and more. Designed for developers, data scientists, researchers, and students with a technical background, DLI training can be accessed in an instructor-led workshop or online in a self-paced course, complete with certification of competency. The DLI University Ambassador Program enables qualified educators to teach DLI workshops at university campuses and academic conferences to faculty, students, and researchers at no cost, complementing the traditional theoretical approaches to university education in machine learning, data science, AI, and parallel computing. 

The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems across autonomous vehicles, digital content creation, healthcare, finance, and more. Designed for developers, data scientists, researchers, and students with a technical background, DLI training can be accessed in an instructor-led workshop or online in a self-paced course, complete with certification of competency. The DLI University Ambassador Program enables qualified educators to teach DLI workshops at university campuses and academic conferences to faculty, students, and researchers at no cost, complementing the traditional theoretical approaches to university education in machine learning, data science, AI, and parallel computing. 

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Topics:
Accelerated Data Science
Type:
Talk
Event:
Supercomputing
Year:
2018
Session ID:
SC1819
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Abstract:
The NVIDIA Deep Learning Institute (DLI) enables engineers, researchers, and scientists to solve problems in applied disciplines with deep learning such as self-driving cars, healthcare, consumer services, and robotics. The DLI instructor-led and online content provides state-of-the-art educational value for university students taking courses in Data Science. Machine Learning, and Artificial Intelligence (AI). The DLI University Ambassador Program is a new initiative where NVIDIA partners with and recognizes select faculty and students as experts in applied Deep Learning using GPUs. The DLI enables these awarded ambassadors to bring this valuable content to their campuses and classrooms themselves through workshops and online labs, complementing the traditional theoretical approaches to teaching in these areas.
The NVIDIA Deep Learning Institute (DLI) enables engineers, researchers, and scientists to solve problems in applied disciplines with deep learning such as self-driving cars, healthcare, consumer services, and robotics. The DLI instructor-led and online content provides state-of-the-art educational value for university students taking courses in Data Science. Machine Learning, and Artificial Intelligence (AI). The DLI University Ambassador Program is a new initiative where NVIDIA partners with and recognizes select faculty and students as experts in applied Deep Learning using GPUs. The DLI enables these awarded ambassadors to bring this valuable content to their campuses and classrooms themselves through workshops and online labs, complementing the traditional theoretical approaches to teaching in these areas.  Back
 
Topics:
HPC and Supercomputing
Type:
Talk
Event:
SIGGRAPH
Year:
2017
Session ID:
SC1717
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Abstract:

Introducing the 3rd Edition of "Programming Massively Parallel Processors – a Hands-on Approach". This new edition is the result of a collaboration between GPU computing experts and covers the CUDA computing platform, parallel patterns, case studies and other programming models. Brand new chapters cover Deep Learning, graph search, sparse matrix computation, histogram and merge sort.
The tightly-coupled GPU Teaching Kit contains everything needed to teach university courses and labs with GPUs.

Introducing the 3rd Edition of "Programming Massively Parallel Processors – a Hands-on Approach". This new edition is the result of a collaboration between GPU computing experts and covers the CUDA computing platform, parallel patterns, case studies and other programming models. Brand new chapters cover Deep Learning, graph search, sparse matrix computation, histogram and merge sort.
The tightly-coupled GPU Teaching Kit contains everything needed to teach university courses and labs with GPUs.

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Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2016
Session ID:
SC6114
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Abstract:
As performance and functionality requirements of interdisciplinary robotics applications rise, industry demand for new graduates familiar with GPU-accelerated computer vision, machine learning and other robotics concepts grows. We'll introduce you to a comprehensive set of academic labs and university teaching material targeted at the NVIDIA Tegra-based Jetson embedded computing platform for use in introductory and advanced interdisciplinary robotics courses. The teaching materials start with the basics and focus on programming the Jetson platform, and include advanced topics such as computer vision, machine learning, robot localization and controls.
As performance and functionality requirements of interdisciplinary robotics applications rise, industry demand for new graduates familiar with GPU-accelerated computer vision, machine learning and other robotics concepts grows. We'll introduce you to a comprehensive set of academic labs and university teaching material targeted at the NVIDIA Tegra-based Jetson embedded computing platform for use in introductory and advanced interdisciplinary robotics courses. The teaching materials start with the basics and focus on programming the Jetson platform, and include advanced topics such as computer vision, machine learning, robot localization and controls.  Back
 
Topics:
Intelligent Machines, IoT & Robotics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6729
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Abstract:

As performance and functionality requirements of interdisciplinary computing applications rise, industry demand for new graduates familiar with accelerated computing with GPUs grows. This webinar introduces a comprehensive set of academic labs and university teaching material for use in courses leveraging introductory and advanced parallel programming concepts. The teaching materials start with the basics and focus on programming GPUs with CUDA, and go on to advanced topics such as optimization, advanced architectural enhancements, and integration of a variety of programming languages.

As performance and functionality requirements of interdisciplinary computing applications rise, industry demand for new graduates familiar with accelerated computing with GPUs grows. This webinar introduces a comprehensive set of academic labs and university teaching material for use in courses leveraging introductory and advanced parallel programming concepts. The teaching materials start with the basics and focus on programming GPUs with CUDA, and go on to advanced topics such as optimization, advanced architectural enhancements, and integration of a variety of programming languages.

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Topics:
Intelligent Machines, IoT & Robotics
Type:
Webinar
Event:
GTC Webinars
Year:
2016
Session ID:
GTCE122
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Abstract:

NVIDIA's GPU Education Outreach Program enables classroom and lab use of NVIDIA technologies. Learn more about how NVIDIA plans to provide teaching materials, real GPU resources and software development tools for academic teaching faculty and system administrators world-wide. We will cover options available to give students access to GPU computing platforms, as well as how educators can access these systems and content. Additionally, we will discuss upcoming education outreach programs and seek feedback on how NVIDIA can help educators more easily teach massively parallel programming to their students or user base.

NVIDIA's GPU Education Outreach Program enables classroom and lab use of NVIDIA technologies. Learn more about how NVIDIA plans to provide teaching materials, real GPU resources and software development tools for academic teaching faculty and system administrators world-wide. We will cover options available to give students access to GPU computing platforms, as well as how educators can access these systems and content. Additionally, we will discuss upcoming education outreach programs and seek feedback on how NVIDIA can help educators more easily teach massively parallel programming to their students or user base.

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Topics:
Programming Languages
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5898
Streaming:
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