Program Outline
Model Parallelism: Building and Deploying Large Neural Networks
Covers patterns for building and deploying large neural networks with model-parallel techniques.
Delivery
Virtual, On-site, or Hybrid
Duration
8 hours
Product
Distributed Deep Learning Frameworks
Role
ML Engineer
NVIDIA
Deep LearningModel Parallelism: Building and Deploying Large Neural Networks
Distributed Deep Learning Frameworks
Best Fit
Audience Profile
Who This Program Is For
Built for advanced teams scaling larger neural networks.
Overview
Program Summary
Official NVIDIA DLI workshop on model parallelism for large neural networks.
Course Outline
Complete Module Sequence
Review the full module sequence for this program, including the primary topic coverage in each module where available.
1Module 1
Scale larger neural networks
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Module 1
Scale larger neural networks
Learn model-parallel approaches for large-model training and deployment.
- Model-parallel fundamentals
- Large-model deployment patterns
Coverage Areas
Topic Coverage
Coverage Item 1
Model-parallel fundamentals
Coverage Item 2
Large-model deployment patterns
Customization
Adapt This Program for Your Team
We can adapt this program around your team structure, platform priorities, delivery goals, and the scenarios your people need to work through in practice.
- •Align to your model stack
- •Add deployment architecture planning
