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Course
- AI
AIOps: Robustness Testing
Ensure your AI applications are reliable and secure. This course will teach you how to implement adversarial testing techniques to improve the robustness of your generative AI models, focusing on practical examples and real-world scenarios to protect against unexpected responses.
What you'll learn
As AI becomes increasingly integrated into critical business operations, ensuring the robustness of AI models is essential. In this course, AIOps: Robustness Testing, you'll learn to implement testing methodologies to build resilient and trustworthy AI applications.
First, you'll explore the fundamentals of adversarial testing and its importance in identifying vulnerabilities in AI systems. Next, you'll discover how to run adversarial attacks to stress test your models, uncovering potential failure points. Finally, you'll learn how to apply techniques like prompt augmentation and chain-of-thought to enhance your model's robustness against malicious inputs. When you're finished with this course, you'll have the skills and knowledge to deploy AI systems that are secure, reliable, and dependable in real-world scenarios.
Table of contents
About the author
Soham is a full stack developer with experience in building large scale web applications and services for clients across the globe.
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