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Verified Information • Last Updated Mar 2026
Red Teaming LLM Applications
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.
Duration
5 Months
Institution
DeepLearning.AI
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into DeepLearning.AI.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$266
Total Est. Investment
$266
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Red Teaming LLM Applications program at DeepLearning.AI are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.