Certifications,
courses, and more

Getting Started with Administering Amazon Quick Suite

Administrator orientation to Amazon Quick Suite, the agentic AI-powered workspace. Covers tenant setup, user and group management, data source connections, governance settings, and monitoring usage and costs.

Amazon Connect AI Self-Service Capabilities

Covers Amazon Connect's AI-powered self-service features, including natural-language IVRs, generative chat and voice bots, and step-by-step guides. Demonstrates how to deflect routine contacts while maintaining a high-quality customer experience.

Advanced Prompt Caching and Response Optimization

This comprehensive course equips developers with advanced techniques for optimizing response times for Large Language Model (LLM) applications using Amazon Bedrock. Through hands-on instruction and practical examples, students will master the intricacies of prompt caching, latency optimization, and intelligent routing strategies essential for building high-performance AI applications.

Building Intelligent Photo Search with AWS AI Services

Hands-on project that builds an intelligent photo search application using AWS AI services such as Amazon Rekognition, Amazon OpenSearch Service, and serverless components for indexing and querying images by content.

Exam Prep Plan Overview: AWS Certified AI Practitioner (AIF-C01 - English)

Overview of the AWS Certified AI Practitioner (AIF-C01) exam prep learning plan, outlining the four exam domains, study resources, and recommended sequence of courses, labs, and practice assessments.

Advanced Tool Use Integration with Amazon Bedrock Models

This training is meant for data engineers and GenAI application developers who want to integrate tools while using Amazon Bedrock (Bedrock) Foundation Models (FM). Upon completing this training, you will understand the concepts of tool integration, the framework used by Bedrock, and best practices for integrating tools with Bedrock.

Agentic AI Framework Deep Dive - Build Multi-Agent Systems

Agentic AI Framework Deep Dive - Model Context Protocol

Agentic AI Framework Deep Dive - Overview

Amazon Bedrock AgentCore Gateway Tutorial

Hands-on tutorial covering Amazon Bedrock AgentCore Gateway, which converts existing APIs and tools into agent-ready capabilities. Walks through configuring inbound and outbound auth, exposing tools to agents, and managing tool catalogs.

Amazon Bedrock AgentCore Getting Started

Introduction to Amazon Bedrock AgentCore, AWS's platform for deploying and operating AI agents at scale. Covers the runtime, gateway, memory, identity, observability, and tools components, and how they work with frameworks such as LangGraph, CrewAI, and Strands.

Amazon Bedrock AgentCore Identity Tutorial

Tutorial on Amazon Bedrock AgentCore Identity, which handles agent authentication and access management. Covers integration with existing identity providers, OAuth-based delegation, and securely scoping agent permissions to downstream services.

Amazon Bedrock AgentCore Memory Tutorial

Tutorial on Amazon Bedrock AgentCore Memory, the managed service for persistent agent context. Covers short-term and long-term memory stores, summarization strategies, and how to maintain personalized state across multi-turn agent interactions.

Amazon Bedrock AgentCore Observability Tutorial

Tutorial on Amazon Bedrock AgentCore Observability, which provides built-in metrics, traces, and logs for AI agents. Covers monitoring runtime, gateway, memory, and identity components and integrating telemetry with CloudWatch and OpenTelemetry-compatible backends.

Amazon Bedrock AgentCore RunTime Tutorial

Tutorial on the Amazon Bedrock AgentCore Runtime, a secure serverless environment for hosting agents. Covers deploying agents, isolating sessions, and using built-in primitives such as the secure browser and code interpreter.

Amazon Bedrock AgentCore Tools Tutorial

Tutorial covering AgentCore's built-in tools, including the secure browser runtime and code interpreter. Walks through how agents use these tools to execute web workflows, run code, and produce visualizations safely at scale.

Amazon Bedrock Business Value and ROI Assessment

Framework for evaluating the business value and return on investment of Amazon Bedrock projects. Covers value driver identification, cost modeling for foundation model usage, and methods for quantifying productivity and revenue impact of generative AI.

Amazon Bedrock Getting Started

Introduction to Amazon Bedrock, AWS's fully managed service for foundation models. Covers available model providers, the playground, key APIs for inference and customization, and core concepts like Knowledge Bases, Agents, and Guardrails.

Amazon Q Developer Command Line Interface (CLI)

In this course, You'll discover how this AI-powered coding assistant integrates directly into your terminal, helping you code, debug, and interact with AWS services more efficiently. By the end of this course, you'll be equipped to leverage Amazon Q Developer CLI to accelerate your development workflow and boost your productivity. Course Objectives In this course, you'll learn about Amazon Q Developer CLI features, capabilities and benefits. Target audience This course is aimed at: Customers and Amazonians Requisites With this being a 100 level offering, there are no requisites Course Outline Module 0: Amazon Q Developer Command Line Interface (CLI) Module 1: Your AI agent in the terminal Module 2: Amazon Q Developer CLI in action Knowledge Check Conclusion

Automate Generative AI workflows using Amazon Bedrock Flows

Demonstrates building automated generative AI workflows with Amazon Bedrock Flows, the visual builder for orchestrating prompts, models, knowledge bases, agents, and Lambda functions into multi-step applications.

Automate the creation of handout notes using Amazon Bedrock Data Automation

Hands-on walkthrough of using Amazon Bedrock Data Automation to extract structured insights from unstructured content and automatically generate handout notes from documents, audio, and video.

AWS for SAP - Generative AI Fundamentals

Foundational course on applying generative AI to SAP workloads running on AWS. Covers integration patterns with Amazon Bedrock, common SAP use cases such as document processing and analytics, and reference architectures.

AWS SimuLearn: Explore the Amazon Bedrock Playgrounds

Simulation-based lab where learners interact with a virtual customer to explore the Amazon Bedrock playgrounds. Provides hands-on experience choosing foundation models and crafting prompts for chat, text, and image use cases.

Batch Processing at Scale With Amazon Bedrock

Covers running large-scale batch inference jobs on Amazon Bedrock, including job submission, input and output formats in S3, cost considerations, and patterns for processing high-volume document and content workloads.