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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.

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