The NVIDIA Deep Learning Institute is offering nine instructor-led workshops at this year’s GTC from April 12-16 on a wide range of advanced software development topics in AI, accelerated computing, and data science. Developers, data scientists, researchers, and students can get practical experience powered by GPUs in the cloud. Upon completion, participants earn an NVIDIA DLI certificate to demonstrate subject matter competency and support career growth.
The full-day workshops offer a comprehensive learning experience that includes hands-on exercises and guidance from expert instructors certified by DLI. These immersive learning experiences are offered live online in many time zones to reach developers worldwide and available in English, Traditional Chinese, Japanese and Korean.
The $249 registration fee includes interactive learning materials, guided instruction, and access to fully configured GPU-accelerated development servers for hands-on exercises.
Register here to DLI workshops at GTC or to view the full schedule. DLI workshops offered at GTC include:
- Fundamentals of Deep Learning — Build the confidence to take on a deep learning project by learning how to train a deep neural network model, work with common data types and model architectures, use transfer learning between models, and more.
- Fundamentals of Accelerated Computing with CUDA C/C++ — Find out how to accelerate CPU-only applications by exposing their latent parallelism on GPUs, using essential techniques like CUDA memory management to optimize accelerated applications.
- Fundamentals of Deep Learning for Multi-GPUs — Scale deep learning training to multiple GPUs, significantly shortening the time required to train neural networks, making solving complex problems with deep learning feasible.
- Accelerating CUDA C++ Applications with Multiple GPUs — Learn how to write CUDA C++ applications that efficiently and correctly utilize all available GPUs in a single node, dramatically improving the performance of applications and making the most cost-effective use of systems with multiple GPUs.
- Fundamentals of Accelerated Data Science with RAPIDS — Learn how to manipulate large data sets directly on the GPU using Dask and cuDF. Apply GPU-accelerated machine learning algorithms including XGBoost, cuGRAPH and cuML to perform data analysis at massive scale.
- Building Transformer-Based Natural Language Processing Applications — Learn about NLP topics like Word2Vec and recurrent neural network-based embeddings, as well as Transformer architecture features and how to improve them. Use pre-trained NLP models for text classification, named-entity recognition and question answering, and deploy refined models for live applications.
- Applications of AI for Anomaly Detection — Discover how to implement multiple AI-based solutions to identify network intrusions, using accelerated XGBoost, deep learning-based autoencoders and generative adversarial networks.
- Deep Learning for Autonomous Vehicles–Perception — Learn how to design, train, and deploy deep neural networks and optimize perception components for autonomous vehicles using the NVIDIA DRIVE development platform.
- Deep Learning for Intelligent Video Analytics — Learn how to build object detection and tracking models to analyze data from large-scale video streams using NVIDIA DeepStream technology. Complete hands-on tasks to build, train, and deploy deep learning models to analyze parking lot camera feeds of a hardware-accelerated traffic management system.
GTC is free to attend and you can register here to access over 1,400 sessions, including short DLI training labs.
Register to reserve your spot to a full-day DLI instructor-led workshop. Space is limited so register early.