Projects
Assignments
Overview
This foundational course introduces the core principles, technologies, and real-world applications of generative AI using AWS services. Learners will gain clarity on where generative AI fits into the modern business landscape and how to implement it responsibly and effectively across use cases.
Objectives
By the end of this course, leaner will be able to:
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Summarize key generative AI concepts, methods, and strategies
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Understand responsible and safe use of generative AI and ML technologies
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Identify appropriate generative AI use cases and solutions
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Discuss foundational model selection and prompt engineering best practices
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Plan and evaluate generative AI project implementation within an organization
Prerequisites
No prior experience with generative AI is required. This course is suitable for beginners and non-technical professionals across:
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Business analysis
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IT support
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Marketing
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Sales
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Product/project management
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Line-of-business or IT management
Course Outline
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Definition and foundations
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AWS generative AI services
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Demo: Generative AI solution
- Identify suitable use cases
- Generative AI applications and use cases
- Explore generative AI use case scenarios
- Use case for class
- Introduction to prompt engineering
- Prompt design best practices
- Advanced prompting strategies
- Model settings and parameters
- Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock
- Introduction to responsible AI
- Core dimensions of responsible AI
- Generative AI considerations
- Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails
- Security overview
- Adverse prompts
- Generative AI security services
- Governance
- Compliance
- Introduction – Generative AI application
- Define a use case
- Select a foundational model
- Improve performance
- Evaluate results
- Deploy the application
- Demo: Amazon Q Business
- Introduction
- Hands-on Lab: Capstone – Creating a Project Plan with Generative AI
- Next steps and additional resources
- Course summary
