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DeepLearning.AI via Coursera

Red Teaming LLM Applications

4.864 ratings at Coursera

Overview

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.

In this course:

1. Explore the nuances of LLM performance evaluation, and understand the differences between benchmarking foundation models and testing LLM applications.

2. Get an overview of fundamental LLM application vulnerabilities and how they affect real-world deployments.

3. Gain hands-on experience with both manual and automated LLM red-teaming methods.

4. See a full demonstration of red-teaming assessment, and apply the concepts and techniques covered throughout the course.

After completing this course, you will have a fundamental understanding of how to experiment with LLM vulnerability identification and evaluation on your own applications.

Syllabus 1

  1. Red Teaming LLM Applications 1.5 hours

    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, an…

Advantages and disadvantages

Advantages

  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • Andrew Ng and his team are among the clearest AI teachers anywhere.
  • Short courses are made with the companies building the tools (OpenAI, Google, AWS, Hugging Face).
  • From DeepLearning.AI, a well-regarded name.
  • Rated 4.8 out of 5 by 64 learners.
  • Self-paced: start any time.

Disadvantages

  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.
  • Short courses are 1–2 hours: an introduction, not mastery.
  • Some notebooks need a paid Pro plan or your own API key.
  • Short (1 hour): an overview, not deep coverage.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

  • Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
  • Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.

Taught by

  • Matteo DoraLead LLM Safety Researcher, Giskard
  • Luca MartialProduct Lead, Giskard

DeepLearning.AI is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (90/100). Andrew Ng's courses.

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