Course Overview
This course explains how to use Model Armor to protect AI applications, specifically large language models (LLMs). The curriculum covers Model Armor's architecture and its role in mitigating threats like malicious URLs, prompt injection, jailbreaking, sensitive data leaks, and improper output handling. Practical skills include defining floor settings, configuring templates, and enabling various detection types. You'll also explore sample audit logs to find details about flagged violations.
Course Objectives
- Explain the purpose of Model Armor in a company’s security portfolio
- Define the protections that Model Armor applies to all interactions with the LLM
- Set up the Model Armor API and find flagged violations
- Identify how Model Armor manages prompts and responses
Who Should Attend?
Security Engineers, AI/ML Developers, and Cloud Architects
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- Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
- Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
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Agenda
- Course Overview
- Model Armor Overview
- Customize Model Armor
- Use Model Armor
- Put It All Together
- Course Conclusion