Generative AI Essentials on AWSGAIEAWAmazon Web ServicesAW-GAIE1.0<p>In this course, you will learn to:</p>
<ul>
<li>Summarize generative AI concepts, methods, and strategies</li><li>Discuss the appropriate use of generative AI and machine learning and their technologies</li><li>Describe how to use generative AI responsibly and safely</li><li>Recognize the types of generative AI solutions with specific use cases</li><li>Explain implementation and project planning of generative AI to your organization</li></ul><p>None</p><p>This course is intended for those with limited prior knowledge of generative AI:</p>
<ul>
<li>Business analysts</li><li>IT supports</li><li>Marketing professionals</li><li>Product or project managers</li><li>Line-of-business or IT managers</li><li>Sales professionals</li></ul><h5>Module 1: Introducing Generative AI</h5><ul>
<li>Generative AI explained</li><li>Foundation models</li><li>AWS generative AI services</li><li>Demo: Generative AI solution</li></ul><h5>Module 2: Exploring Generative AI Use Cases</h5><ul>
<li>Identify suitable use cases</li><li>Generative AI applications and use cases</li><li>Explore generative AI use case scenarios</li><li>Use case for class</li></ul><h5>Module 3: Essentials of Prompt Engineering</h5><ul>
<li>Introduction to prompt engineering</li><li>Prompt design best practices</li><li>Advanced prompting strategies</li><li>Model settings and parameters</li><li>Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock</li></ul><h5>Module 4: Responsible AI Principles and Considerations</h5><ul>
<li>Introduction to responsible AI</li><li>Core dimensions of responsible AI</li><li>Generative AI considerations</li><li>Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails</li></ul><h5>Module 5: Security, Governance, and Compliance</h5><ul>
<li>Security overview</li><li>Adverse prompts</li><li>Generative AI security services</li><li>Governance</li><li>Compliance</li></ul><h5>Module 6: Implementing Generative AI Projects</h5><ul>
<li>Introduction – Generative AI application</li><li>Define a use case</li><li>Select a foundational model</li><li>Improve performance</li><li>Evaluate results</li><li>Deploy the application</li><li>Demo: Amazon Q Business</li></ul><h5>Module 7: Integrating Generative AI into the Development Lifecycle</h5><ul>
<li>Introduction</li><li>Hands-on Lab: Capstone – Creating a Project Plan with Generative AI</li></ul><h5>Module 8: Course Wrap-up</h5><ul>
<li>Next steps and additional resources</li><li>Course summary</li></ul><h5>Module 1: Introducing Generative AI</h5><ul>
<li>Generative AI explained</li><li>Foundation models</li><li>AWS generative AI services</li><li>Demo: Generative AI solution</li></ul><h5>Module 2: Exploring Generative AI Use Cases</h5><ul>
<li>Identify suitable use cases</li><li>Generative AI applications and use cases</li><li>Explore generative AI use case scenarios</li><li>Use case for class</li></ul><h5>Module 3: Essentials of Prompt Engineering</h5><ul>
<li>Introduction to prompt engineering</li><li>Prompt design best practices</li><li>Advanced prompting strategies</li><li>Model settings and parameters</li><li>Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock</li></ul><h5>Module 4: Responsible AI Principles and Considerations</h5><ul>
<li>Introduction to responsible AI</li><li>Core dimensions of responsible AI</li><li>Generative AI considerations</li><li>Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails</li></ul><h5>Module 5: Security, Governance, and Compliance</h5><ul>
<li>Security overview</li><li>Adverse prompts</li><li>Generative AI security services</li><li>Governance</li><li>Compliance</li></ul><h5>Module 6: Implementing Generative AI Projects</h5><ul>
<li>Introduction – Generative AI application</li><li>Define a use case</li><li>Select a foundational model</li><li>Improve performance</li><li>Evaluate results</li><li>Deploy the application</li><li>Demo: Amazon Q Business</li></ul><h5>Module 7: Integrating Generative AI into the Development Lifecycle</h5><ul>
<li>Introduction</li><li>Hands-on Lab: Capstone – Creating a Project Plan with Generative AI</li></ul><h5>Module 8: Course Wrap-up</h5><ul>
<li>Next steps and additional resources</li><li>Course summary</li></ul>In this course, you will learn to:
- Summarize generative AI concepts, methods, and strategies
- Discuss the appropriate use of generative AI and machine learning and their technologies
- Describe how to use generative AI responsibly and safely
- Recognize the types of generative AI solutions with specific use cases
- Explain implementation and project planning of generative AI to your organizationNoneThis course is intended for those with limited prior knowledge of generative AI:
- Business analysts
- IT supports
- Marketing professionals
- Product or project managers
- Line-of-business or IT managers
- Sales professionalsModule 1: Introducing Generative AI
- Generative AI explained
- Foundation models
- AWS generative AI services
- Demo: Generative AI solution
Module 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
Module 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
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
Module 5: Security, Governance, and Compliance
- Security overview
- Adverse prompts
- Generative AI security services
- Governance
- Compliance
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
Module 7: Integrating Generative AI into the Development Lifecycle
- Introduction
- Hands-on Lab: Capstone – Creating a Project Plan with Generative AI
Module 8: Course Wrap-up
- Next steps and additional resources
- Course summaryModule 1: Introducing Generative AI
- Generative AI explained
- Foundation models
- AWS generative AI services
- Demo: Generative AI solution
Module 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
Module 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
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
Module 5: Security, Governance, and Compliance
- Security overview
- Adverse prompts
- Generative AI security services
- Governance
- Compliance
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
Module 7: Integrating Generative AI into the Development Lifecycle
- Introduction
- Hands-on Lab: Capstone – Creating a Project Plan with Generative AI
Module 8: Course Wrap-up
- Next steps and additional resources
- Course summary1 jour490.00750.00900.00750.00750.001300.00700.00500.00850.00960.00695.00700.00865.00