Program Outline
Accelerating End-to-End Data Science Workflows
Covers applied acceleration patterns across the end-to-end data science lifecycle using NVIDIA tooling.
Delivery
Virtual, On-site, or Hybrid
Duration
2 hours
Product
NVIDIA RAPIDS
Role
Data Scientist
NVIDIA
Data ScienceAccelerating End-to-End Data Science Workflows
NVIDIA RAPIDS
Best Fit
Audience Profile
Who This Program Is For
Built for teams that want broader workflow acceleration instead of isolated experimentation.
Overview
Program Summary
Official NVIDIA DLI self-paced course on end-to-end accelerated data science workflows.
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
Speed up the full lifecycle
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Module 1
Speed up the full lifecycle
Explore end-to-end acceleration opportunities across preparation, modeling, and iteration.
- Workflow acceleration map
- End-to-end performance patterns
Coverage Areas
Topic Coverage
Coverage Item 1
Workflow acceleration map
Coverage Item 2
End-to-end performance 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.
- •Use your own workflow bottlenecks
- •Add platform adoption guidance
