Curriculum
- 1 Section
- 8 Lessons
- 1 Day
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- Topics8
- 1.1Module 1: Introducing Generative AI Generative AI explained Foundation models AWS generative AI services Demo: Generative AI solution
- 1.2Module 2: Exploring Generative AI Use Cases Identify suitable use cases Generative AI applications and use cases Explore generative AI use case scenarios Use case for class
- 1.3Module 3: Essentials of Prompt Engineering Introduction to prompt engineering Prompt design best practices Advanced prompting strategies Model settings and parameters Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock
- 1.4Module 4: Responsible AI Principles and Considerations Introduction to responsible AI Core dimensions of responsible AI Generative AI considerations Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails
- 1.5Module 5: Security, Governance, and Compliance Security overview Adverse prompts Generative AI security services Governance Compliance
- 1.6Module 6: Implementing Generative AI Projects Introduction – Generative AI application Define a use case Select a foundational model Improve performance Evaluate results Deploy the application Demo: Amazon Q Business
- 1.7Module 7: Integrating Generative AI into the Development Lifecycle Introduction Hands-on Lab: Capstone – Creating a Project Plan with Generative AI
- 1.8Module 8: Course Wrap-up Next steps and additional resources Course summary
Module 4: Responsible AI Principles and Considerations Introduction to responsible AI Core dimensions of responsible AI Generative AI considerations Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails
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Module 6: Implementing Generative AI Projects Introduction – Generative AI application Define a use case Select a foundational model Improve performance Evaluate results Deploy the application Demo: Amazon Q Business
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