New course with DeepLearningAI: Red Teaming LLM Applications

Our new course in collaboration with DeepLearningAI team provides training on red teaming techniques for Large Language Model (LLM) and chatbot applications. Through hands-on attacks using prompt injections, you'll learn how to identify vulnerabilities and security failures in LLM systems.

Hi there,

The Giskard team hopes you're having a good week!

This month we have the pleasure to announce our new course on Red Teaming LLM Applications in collaboration with Andrew Ng and the DeepLearning.ai team!

Learn how to make safer LLM apps. Enroll for free 👉 here.

What you’ll learn in this course 🤓

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, and:

Explore the nuances of LLM performance evaluation, and understand the differences between benchmarking foundation models and testing LLM applications.
Get an overview of fundamental LLM application vulnerabilities and how they affect real-world deployments.
Gain hands-on experience with both manual and automated LLM red-teaming methods.
See a full demonstration of red-teaming assessment, and apply the concepts and techniques covered throughout the course.

Get a sneak peek of the course in this video 🎥

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👉 Enroll for free here

Happy LLM evaluation!

Thank you so much, and see you soon! ❤️

The Giskard Team 🐢

Continuously secure LLM agents, preventing hallucinations and security issues.

Book a demo

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