Program Outline
Exploring Adversarial Machine Learning
Introduces adversarial machine learning concepts, attacks, and applied robustness considerations.
Delivery
Virtual, On-site, or Hybrid
Duration
2 hours
Product
Deep Learning Frameworks
Role
ML Engineer
NVIDIA
Deep LearningExploring Adversarial Machine Learning
Deep Learning Frameworks
Best Fit
Audience Profile
Who This Program Is For
Built for teams responsible for AI robustness and model security.
Overview
Program Summary
Official NVIDIA self-paced course exploring adversarial machine learning.
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
Study adversarial ML risks
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Module 1
Study adversarial ML risks
Learn core adversarial concepts and what they mean for deployed model robustness.
- Adversarial attack basics
- Robustness considerations
Coverage Areas
Topic Coverage
Coverage Item 1
Adversarial attack basics
Coverage Item 2
Robustness considerations
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 model-security scenario
