Learn how to test and find vulnerabilities in your LLM applications to make them safer. In this course, you’ll attack various chatbot applications using prompt injections to see how the system reacts and understand security failures. LLM failures can lead to legal liability, reputational damage, and costly service disruptions. This course helps you mitigate these risks proactively. Learn industry-proven red teaming techniques to proactively test, attack, and improve the robustness of your LLM applications.
(15 reviews)
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What you'll learn
Learn to identify and evaluate vulnerabilities in large language model (LLM) applications.
Apply red teaming techniques from cybersecurity to ensure the safety and reliability of your LLM application.
Use an open source library from Giskard to help automate LLM red-teaming methods.
Skills you'll practice
Details to know
Only available on desktop
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About this project
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How you'll learn
Hands-on, project-based learning
Practice new skills by completing job-related tasks with step-by-step instructions.
No downloads or installation required
Access the tools and resources you need in a cloud environment.
Available only on desktop
This project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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