Generative AI Essentials on AWS is a comprehensive one-day, instructor-led training course designed for professionals with limited prior knowledge of generative AI. The course covers foundational concepts in responsible AI, provides practical experience with AWS generative AI services ( Amazon Bedrock, Amazon Nova 2, Amazon Bedrock Knowledge Bases, and Amazon Bedrock AgentCore). Participants gain hands-on implementation experience with responsible AI principles through Amazon Bedrock Guardrails. Responsible AI serves as a foundational theme throughout all modules, connecting ethical principles to technical implementation. Participants progress from understanding AI fundamentals through implementing solutions, exploring agentic AI capabilities, understanding security and governance considerations, and describing project planning components. Approximately 40% of course time is dedicated to hands-on labs and demonstrations.
Course Objectives
- Explain responsible AI foundations
- Describe multimodal AI capabilities
- Implement generative AI solutions using Amazon Bedrock and Amazon Nova 2
- Explain how retrieval-augmented generation (RAG) enhances AI responses by connecting agents to organizational knowledge sources
- Describe Amazon Bedrock AgentCore capabilities
- Apply responsible AI practices using Amazon Bedrock Guardrails
- Explain security and governance considerations
- Describe key components of generative AI project planning
Who Should Attend
- Business analyst
- IT support
- Marketing professional
- Product or project manager
- Line-of-Business or IT Managers
- Sales professionals
Prerequisites
None – No prior AI or generative AI knowledge required
Course Outline
Module 0: Course Introduction
- Course structure/schedule
- Five-phase learning journey
- Responsible AI foundational theme
Module 1: Responsible AI Foundations
- AI evolution: from traditional to generative
- Eight dimensions of responsible AI
- AWS commitment to responsible AI
Module 2: Introducing Generative AI
- Generative AI Foundation
- Foundation models and embeddings deep dive
- Amazon Bedrock and Amazon Nova 2 models
- Comparing models
Module 3: Multi-Modal AI and use cases
- Multimodal AI capabilities
- Industry applications and use cases
- Use case evaluation framework
Module 4: Essentials of prompt engineering
- Prompt engineering fundamentals
- Prompting strategies
- Prompt security and attach vectors
Lab 1 – Optimizing Slogan Generation with Amazon Bedrock
Module 5: Implementing responsible AI with Amazon Bedrock Guardrails
- Amazon Bedrock guardrails overview and configuration
Lab 2 – Implementing Responsible AI Principles with Amazon Bedrock Guardrails
Module 6: Introduction to Amazon Agents
- Agentic AI concepts
- Amazon Bedrock capabilities
- Amazon Bedrock AgentCore overview
- RAG and Knowledge Bases
Module 7: Introduction to Security, Governance, and Compliance
- From security principles to organizational accountability
- Governance frameworks
- Compliance requirements
Module 8: Implementing generative AI projects
- Project planning fundamentals
Lab 3: Building an HR Assistant with Amazon Bedrock
Module 9: Summary
- Learning journey recap
- Next steps
