Certifications,
courses, and more

Evaluate and Enhance RAG Performance with Amazon Bedrock

Covers evaluating and improving retrieval-augmented generation systems built on Amazon Bedrock, including retrieval and generation metrics, chunking and re-ranking strategies, and using Bedrock model evaluation tools.

Exploring Amazon Nova models using Amazon Bedrock

Tour of the Amazon Nova family of foundation models on Amazon Bedrock, covering Nova Micro, Lite, Pro, and multimodal variants, their capabilities, and usage patterns for text, image, and video tasks.

Generative BI with Amazon Q in Quicksight - Getting Started

Amazon Q in QuickSight introduces a new suite of business intelligence (BI) capabilities by using the large language models (LLMs) of Amazon Bedrock and combining them with the capabilities of Amazon QuickSight. In this course, you will learn about technical concepts and the benefits of using Amazon Q in QuickSight. You will learn about the architecture of Amazon Q in QuickSight and how the built-in features help you to build dashboards and derive insights from your data with natural language queries. Course level: Fundamental. Duration: 60 minutes. This course includes presentations, demonstrations, and assessments.

Increasing Application Security with Bedrock Guardrails and GenAI

Demonstrates using Amazon Bedrock Guardrails to harden GenAI-enabled applications, covering content filtering, denied topics, PII redaction, and contextual grounding checks for production-grade safety.

Integrating Amazon Bedrock powered Agents with Model Context Protocol Servers using the Strands Agents SDK

Walkthrough of connecting Amazon Bedrock-powered agents to Model Context Protocol (MCP) servers using the Strands Agents SDK, enabling agents to access external tools and data sources via a standardized protocol.

Introduction to Amazon Bedrock: Foundation Models and AI Applications

Introductory tour of Amazon Bedrock, covering available foundation models, the Bedrock playground, key APIs, and how to compose models with knowledge bases, agents, and guardrails to build AI applications.

Mastering Model Evaluation in Amazon Bedrock: From Basics to Best Practices

Comprehensive coverage of model evaluation in Amazon Bedrock, including automatic and human-in-the-loop evaluation jobs, choosing metrics, designing evaluation datasets, and operationalizing model selection.

Prompt Engineering Best Practices for Amazon Bedrock Models

Practical prompt engineering best practices tailored to foundation models available on Amazon Bedrock, including model-specific prompt formats, system prompts, structured outputs, and techniques like chain-of-thought and self-consistency.

Query Amazon Aurora PostgreSQL using Amazon Bedrock Knowledge Bases structured data

Demonstrates using Amazon Bedrock Knowledge Bases with structured data backed by Amazon Aurora PostgreSQL, enabling natural-language queries over relational data with grounded SQL generation and result synthesis.

Streamline GitHub workflows with generative AI using Amazon Bedrock and MCP

Demonstrates streamlining GitHub workflows using Amazon Bedrock and Model Context Protocol (MCP) servers, including generating pull request reviews, automating issue triage, and connecting agents to repository tools.

Claude with Amazon Bedrock