Aws Bedrock Complete Guide: Foundation Models, Agents

Learn AWS Bedrock, foundation models, agents, flows, LLMOps, and industry use cases to build and scale real-world AI

What you'll learn

Understand AWS Bedrock fundamentals, foundation models, and how they power AI applications.

Learn to design, build, and deploy AI solutions using Bedrock APIs, agents, and workflows.

Gain skills in Bedrock optimization, troubleshooting, monitoring, and LLMOps best practices.

Apply Bedrock to real-world industry use cases and prepare for AWS AI/ML certifications.

Requirements

Basic knowledge of cloud computing is helpful, but no prior AWS or AI/ML experience is required.

Description

Artificial Intelligence is transforming the way businesses operate, and AWS Bedrock is at the center of this change. This course is designed to take you from the fundamentals of AWS Bedrock to advanced concepts like agents, flows, LLMOps, and industry-specific applications. Whether you are a beginner exploring AI, a developer building real-world solutions, or a professional preparing for certification, this course provides you with the skills and knowledge needed to succeed.You’ll begin with an introduction to foundation models and how AWS Bedrock delivers them as a fully managed, serverless service. Step by step, we’ll explore prompts, prompt engineering, intelligent routing, model evaluation, security, and monitoring. You’ll also learn advanced strategies such as chunking, re-ranking, data automation, and troubleshooting to optimize performance.The course includes a dedicated focus on Bedrock Agents, MCP, and inter-agent communication, along with a comparison between Bedrock and other AWS services like SageMaker. We’ll also cover Bedrock Nova, ACT models, and reasoning models for next-gen AI applications.By the end of this course, you will be confident in designing, deploying, and scaling AI-powered applications with AWS Bedrock. You’ll also gain valuable insights into Bedrock pricing, industry use cases, and certification preparation, giving you a complete roadmap to mastery.This course blends theory, hands-on learning, and practical guidance, making it ideal for students, developers, cloud professionals, and AI enthusiasts who want to leverage AWS Bedrock to build the future of AI.

Overview

Section 1: Introduction

Lecture 1 Course Introduction

Lecture 2 What is Bedrock?

Lecture 3 Designing Solution with Foundation Models in Bedrock and Marketplace.

Lecture 4 Building Solutions with Amazon Bedrock - Solution Library , Well Architected

Lecture 5 Working with Knowledge Base and agents

Lecture 6 What are prompts and Prompt engineering ?

Lecture 7 API and Extensibility

Lecture 8 What is Q and how is it related to Bedrock ?

Lecture 9 Bedrock Security

Lecture 10 Bedrock Pricing

Lecture 11 Amazon Nova and ACT model

Lecture 12 Bedrock Agents and MCP

Lecture 13 FM – Reasoning Models and Frontier Reasoning

Lecture 14 Bedrock Data Automation

Lecture 15 Sagemaker Unified Studio

Lecture 16 Bedrock Flows

Lecture 17 Bedrock Re-ranker Model

Lecture 18 Chunking Strategy in bedrock

Lecture 19 Bedrock Troubleshooting and Debugging

Lecture 20 Bedrock - DevOps, LLMOPS - Quick Perspective

Lecture 21 Bedrock Prompt Optimization and Bedrock intelligent Routing

Lecture 22 Bedrock Model Evaluation – LLM as Judge

Lecture 23 Bedrock Monitoring

Lecture 24 Bedrock Model Distillation

Lecture 25 Bedrock Vibe Coding

Lecture 26 Agentic AI - Open Protocols for Agent – MCP and Strand Agents

Lecture 27 Bedrock Agentcore

Lecture 28 Bedrock Industry Use cases

Lecture 29 Course Debrief and Next Steps

Section 2: Additional content

Lecture 30 Bedrock and AI Certification

Lecture 31 AWS Skill Builder and Bedrock

Lecture 32 How to Build solution with bedrock

Section 3: References

Lecture 33 Bedrock Key Resources

This course is for students, developers, cloud professionals, and AI enthusiasts who want to master AWS Bedrock, build real-world AI solutions, and prepare for certifications.