If AI, data science, graphics or robotics is your jam, stream the NVIDIA AI Essentials Learning Series this summer.
These intro-level courses provide foundational knowledge to students and early-career developers looking to broaden their areas of expertise. The free series includes over a dozen sessions — each less than an hour long — on topics including conversational AI, ray tracing and robotics fundamentals.
For a deeper dive, register for daylong hands-on courses from the NVIDIA Deep Learning Institute and earn a certificate of competency to boost your resume. To date, DLI has trained more than 300,000 developers through an extensive catalog of self-paced and instructor-led courses and workshops.
Besides picking up new skills to boost your career journey, there are summer sweepstakes at stake: For every 30 minutes a participant watches the learning series, they earn an entry to win a DLI book and free registration codes for self-paced courses.
For those who register for DLI courses on deep learning, accelerated data science and AI on the NVIDIA Jetson Nano, we’re upping the game. Upon successful completion of one or more of these courses, participants will be entered to win an NVIDIA GeForce RTX 3090 GPU in addition to three DLI registration codes and the book.
Here’s a taste of what students, educators and early-career technologists will find in the learning series.
This talk covers what deep learning is, what it’s good for and why it’s such a powerful technology. Will Ramey, senior director and global head of developer programs at NVIDIA, talks through the different types of neural networks and explains how they’re trained, optimized and deployed in industries like healthcare and energy. He also discusses some of the challenges organizations face when adopting deep learning.
Ray tracing brings stunning, realistic visuals to the movie and gaming industries — but how does it work? In this session, NVIDIA researcher Pete Shirley guides viewers through the process of writing code to generate a ray-traced image of a 3D scene. As he goes, Shirley explains key concepts that form the foundation of ray tracing.
Building a conversational AI model requires developers to achieve two key features: high accuracy and low latency. This session provides an overview of conversionational AI models for automatic speech recognition, natural language processing and text-to-speech. Meriem Bendris, a solution architect at NVIDIA, shares how to train and fine-tune these models using NVIDIA NeMo, the Transfer Learning Toolkit and the NVIDIA Riva application framework.
Learn how to get started from scratch with the NVIDIA Jetson Nano 2GB developer kit — even if you’re not a developer. This crash course, led by NVIDIA’s Asier Arranz Jiminez, walks through the process from installation to inference with an AI model that detects vehicles, roads and pedestrians.
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