Getting Started with Amazon Bedrock

Übersicht

Getting Started with Amazon Bedrock is a foundational course designed for developers, data professionals, and AI enthusiasts seeking to build expertise in generative AI using AWS’s fully managed service—Amazon Bedrock. This course focuses on the key components of the Bedrock platform, including foundation model selection, responsible AI principles, Retrieval-Augmented Generation (RAG), agent orchestration, automation, and integration with AWS services.

Through a structured and interactive learning path, you’ll gain hands-on experience developing AI-powered applications, managing secure workflows, and understanding the tools necessary to scale generative AI in production environments. Whether you're just beginning your journey in AI or preparing for AWS certification in machine learning, this course provides the core skills and practical insight needed to succeed in the evolving landscape of generative AI.

This course includes approximately 5:

30–6:

00 hours of video lectures, combining both foundational theory and real-world demonstrations. It is divided into three comprehensive modules, each broken down into focused lessons that progressively build your knowledge of Bedrock's capabilities.

To assess learning progress, each module includes interactive quizzes and in-video practice questions that reinforce key concepts and application skills. 📘 Module 1:

Amazon Bedrock Fundamentals 🧠 Module 2:

RAG, Safety & Agents ⚙️ Module 3:

Automation, Monitoring & Careers

Lehrplan

• Amazon Bedrock Fundamentals
This week, we’ll explore the foundational elements of Amazon Bedrock, AWS’s fully managed service for building and scaling generative AI applications with foundation models. You’ll gain a clear understanding of how Bedrock fits into the broader AWS ecosystem and supports serverless, customizable AI solutions.
• RAG, Safety & Agents
In Week 2, we’ll shift our focus to Retrieval-Augmented Generation (RAG), safety mechanisms, and agent-based orchestration in Amazon Bedrock. You’ll begin by understanding the architecture and principles behind RAG and how it enhances large language model (LLM) outputs with external knowledge sources.
• Automation, Monitoring & Careers
Welcome to Week 3! This final module focuses on advanced topics including workflow automation, system integration, and career development within the Amazon Bedrock ecosystem. You’ll learn how to streamline generative AI processes using Amazon Bedrock Flows and implement data-driven automation through Bedrock Data Automation (BDA).

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Unterrichtet von

Whizlabs Instructor

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Fachgebiete

Programming