DLI ワークショップでハンズオン トレーニングを受講する

Monday, March 20
6:00 a.m. -  2:00 p.m. PDT

Fundamentals of Deep Learning

Learn the key techniques and tools required to train a deep learning model through hands-on exercises in computer vision and natural language processing.

Monday, March 20
9:00 a.m. - 5:00 p.m. PDT

Scaling CUDA C++ Applications to Multiple Nodes

Learn the tools and techniques needed to write NVIDIA® CUDA® C++ applications that can scale efficiently to clusters of NVIDIA GPUs.  

Monday, March 20
6:00 a.m. - 2:00 p.m. PDT

Building Transformer-Based Natural Language Processing Applications

Learn how to use natural language processing transformer-based models for “text classification” tasks.

Wednesday, March 22
6:00 a.m. - 2:00 p.m. PDT

Fundamentals of Accelerated Data Science

Learn how to build and execute end-to-end GPU-accelerated data science workflows that let you quickly explore, iterate, and get work into production.

Wednesday, March 22
9:00 a.m. - 5:00 p.m. PDT

Building Conversational AI Applications

Learn how to quickly build and deploy production-quality conversational AI applications with real-time transcription and natural language processing (NLP) capabilities.

Wednesday, March 22
6:00 a.m. - 2:00 p.m. PDT

Data Parallelism: How to Train Deep Learning Models on Multiple GPUs

Discover the techniques for data-parallel deep learning training on multiple GPUs and work with deep learning tools, frameworks, and workflows to perform neural network training. 

Wednesday, March 22
9:00 a.m. -  5:00 p.m. PDT

Fundamentals of Deep Learning

Learn the key techniques and tools required to train a deep learning model through hands-on exercises in computer vision and natural language processing.

Thursday, March 23
9:00 a.m. - 5:00 p.m. PDT

Model Parallelism: Building and Deploying Large Neural Networks  

Learn how to train the largest of neutral networks and deploy them to production using techniques to overcome the challenges associated with large-model memory footprint.

Thursday, March 23
6:00 a.m. - 2:00 p.m. PDT

Computer Vision for Industrial Inspection

Build a deep learning model to automate the verification of capacitors in an NVIDIA printed circuit board (PCB) using a real production dataset. Lower the verification cost and increase the production across various use cases.  

Monday, March 20
9:00 a.m. - 5:00 p.m. CET

Fundamentals of Deep Learning

Learn the key techniques and tools required to train a deep learning model through hands-on exercises in computer vision and natural language processing.

Monday, March 20
9:00 a.m. - 5:00 p.m. CET 

Data Parallelism: How to Train Deep Learning Models on Multiple GPUs

Discover the techniques for data-parallel deep learning training on multiple GPUs and work with deep learning tools, frameworks, and workflows to perform neural network training.  

Monday, March 20
9:00 a.m. - 5:00 p.m. CET

Fundamentals of Accelerated Computing With CUDA Python

Learn the fundamental tools and techniques for running GPU-accelerated Python applications using CUDA GPUs and the Numba compiler.

Wednesday, March 22
9:00 a.m. - 5:00 p.m. CET

Model Parallelism: Building and Deploying Large Neural Networks 

Learn how to train the largest neutral networks and deploy them to production using techniques to overcome the challenges associated with a large-model memory footprint.

Monday, March 20
9:00 a.m. - 5:00 p.m. CET 

Applications of AI for Anomaly Detection  

Learn about multiple AI based solutions that solve important telecommunications problems by identifying network intrusions. 

Wednesday, March 22
9:00 a.m. - 5:00 p.m. CET

Applications of AI for Predictive Maintenance

Identify key challenges around detecting anomalies that can lead to costly breakdowns with AI-based predictive maintenance.