In its bid to train future market leaders global giant in Visual Computing Technologies, Nvidia has mounted efforts to train developers in artificial intelligence (AI) and machine learning (ML) at its Deep Learning Institute.
The announcement came in the recently concluded annual GPU Technology Conference in San Jose, California, aims to train over 1 lakh developers.
The Deep Learning Institute by Nvidia that was started in 2015 comprises of both hands-on training sessions and online courses for AI enthusiasts. The initial sessions for the program were offered at various GTC conferences across various cities, the key attraction being the Indian and Chinese ones. These hands-on sessions delivered during global series of GTC conferences in seven cities delivered more than 18,000 hours of training during a span of two years.
(NVIDIA, Credit: Google)
In the US alone, the institute has trained developers across companies like Adobe, Alibaba, SAP, government institutions including the National Institutes of Health (NIH), National Institute of Science and Technology (NIST). In India, it has reached the Indian Institute of Technology, Mumbai.
However, the company, in late 2016, made available online courses in collaboration with Coursera, Microsoft and Udacity. It now intends to train up to 1 lakh data scientists and developers in mastering their skills not only in machine learning workflows but in using deep neural networks to solve complex real-world modeling problems.
Nvidia course offerings
The topics of the course revolve around becoming a self-driving car engineer, creating smarter robots using deep learning with tools like Microsoft Azure, predicting the risk of a disease, preventing it and more.
It also includes instructor-led seminars, workshops, classes that reach developers across Asia, Europe and US. The hands-on training would be taught by certified experts from Nvidia partnering companies and universities, wherein they cover fundamentals of deep learning with topics like AI for object detection and image classification with TensorFlow, neural network deployment with DIGITS, and inference optimization for autonomous vehicles with TensorRT. The virtual classes are delivered through high-performance Amazon Web Services and Google’s Qwiklabs.
With the number of training hours per person increasing along with the number of training labs, Nvidia plans to certify the engineering competence in the labs it now offers within the next year. The various areas of instruction include health care, self-driving cars, web services, robotics, video analytics, and financial services.
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