Example Curriculum
Introduction
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- Ultimate AWS Bedrock Guide: Build & Scale Generative AI Apps (1:54)
- Course Overview (8:44)
- Course Projects Explained
- Capstone Project 1 Overview: Building Multi Agentic Workflows (10:12)
- Capstone Project 2: Building Interruptible Voice Agents (6:56)
- Github Links to All Course Resources
- Course Updates
- Exercise: Meet Your Classmates and Instructor
- Course Resources
Initial Setup
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Getting Started with AWS Bedrock
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- Introduction to Bedrock Foundation Models (16:12)
- Deep Dive Into Inference Configurations (26:37)
- Inference Profiles, Model Catalog, Provisioned Throughput and More Theory (18:06)
- Prompt Management, Optimization, and More (18:50)
- Exploring the Playground in AWS Bedrock (16:19)
- Exploring Modal Providers, Modalities, API Invocation and Pricing (15:31)
- Quotas, Model Comparison, Guardrails, and More (27:33)
- Image Generation in the Playground with Diffusion Models (2:54)
Code Generation Project
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- Setting Up the Code Generation Project (1:05)
- Coding our Lambda Function and Integrating with AWS Bedrock (17:51)
- Setting up API Gateway and our Serverless Stack (5:34)
- Testing our Live Endpoint (5:57)
- Creating our Boto3 Lambda Layer (2:23)
- Attaching our Lambda Layer to our Function (2:24)
- Testing our Bedrock Model (6:28)
- Verifying Final Output of Bedrock (2:24)
Meeting Notes Summarisation Project with Bedrock
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- Setting up our Lambda Function with Bedrock for Content Summarization (8:43)
- Finishing our Lambda Function for Meeting Summarisation (14:10)
- Creating new API Gateway Endpoint for this Lambda Function (2:15)
- Invoking our Serverless Meeting Notes Summarisation Endpoint (6:30)
- Analyzing the Final Results (1:39)
Using Diffusion Models with Bedrock for Image Creation
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Evaluating Large Language Model Performance with AWS Bedrock Evaluator
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Retrieval Augmented Generation (RAG) with AWS Bedrock
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- Introduction to AWS Bedrock Knowledge Base (2:57)
- Retrieval Augmented Retrieval (RAG) Overview (6:40)
- Setting Up Our Own Knowledge Base - Part 1 (8:08)
- Setting Up Our Own Knowledge Base - Part 2 (0:50)
- Testing our Bedrock Knowledge Base with Antropic's Claude Model (7:20)
- Clean Up Resources (1:10)
- API Resources (0:42)
Cleanup
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Building Multi-Agentic AI Workflow
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- Architecture Diagram of Our Multi Agentic Workflow (6:41)
- LLM Model Access, API Rate Limits, Quotas, and AWS Regions (7:47)
- Introduction to AWS Bedrock Agents (1:04)
- Creating the Restaurant Agent (17:33)
- Creating our AWS S3 Bucket To Store Our Data (4:04)
- Uploading Restaurant Data to AWS S3 (0:48)
- Creating an Action Group For Our Restaurant Agent (13:01)
- Finishing Our Lambda Function for our Restaurant Agent (12:26)
- Testing Our Restaurant Agent (14:38)
- Setting Up the Accommodation Agent (8:45)
- Uploading Our Hotel and Airbnb Data to AWS S3 (1:14)
- Creating The Lambda Function Action Group For The Accommodation Agent (17:41)
- Finishing Our Accommodation Agent (9:49)
- Testing the Accommodation Agent (8:20)
- Creating and Testing The Supervisor Agent (9:00)
- Explaining Agent Collaborators (4:41)
- Multi Agent UI Enhancement, Timing Agents (2:51)
- Serverless Invocation of the Supervisor Agent using AWS Lambda (11:51)
- Setting up AWS API Gateway to Deploy Our Worfklow Through the Internet (3:24)
- Testing Our Endpoint Through The Internet with Postman (5:14)
- Cleaning Up Resources (2:29)
Deploying Agents with AWS Bedrock AgentCore
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- What is AWS Bedrock Agent Core (10:51)
- Bedrock Agent Core Course Resources
- Accessing AgentCore via Sagemaker AI Setup (1:33)
- Finishing SagemakerAI Setup (2:53)
- AWS Bedrock Agent Core Architecture Diagram
- Creating our Test Agent (14:51)
- Testing Our Agent (5:20)
- Configuring the AgentCore Runtime (9:09)
- Deploying the Agent to AgentCore (8:36)
- Tracing the Agent Logs in CloudWatch for Observability (15:46)
- Don't forget to shutdown the SagemakerAI Server (0:33)
- Session Management for Agents (7:51)
- Understanding AgentCore Sessions (5:57)
- Lifecycle Management for AgentCore Sessions (4:13)
- Cost Calculations for AgentCore Runtime (3:08)
- Understanding Costs
Adding Short and Long Term Memory To Bedrock Agents via Bedrock AgentCore
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- Understanding Short Term Memory (10:06)
- Short Term Memory Imports (7:53)
- Create the Resources for Short Term Memory (6:42)
- Verify Agent Memory Creation in the UI (0:54)
- Implementing Memory Hooks (11:07)
- Creating the Duck Duck Go Web Search Agent (1:24)
- Testing our Short Term Memory Agent (12:18)
- Understanding the Pricing of Short Term Memory (1:36)
- Introduction to Long Term Memory (2:35)
- Long Term Memory Strategies: Semantic, Preferences and Summaries (5:51)
- Inspecting Short Term Memory (6:37)
- Inspecting Long Term Memory (6:49)
- Testing our Agent with a Combined Short and Long Term Memory (11:59)
- Long Term Memory Pricing (1:29)
2026 Updates: Reinforcement Fine Tuning, BDA, Prompt Router, Batch Mode + more
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- Prompt Management with AWS Bedrock (14:39)
- Watermark Detection, Was this image Created with AI? (1:52)
- Detail About Upcoming Video
- Reinforcement Fine Tuning with AWS Bedrock (18:24)
- Data Automation, Intelligent Document, Video, Image, and Audio Processing Part 1 (14:01)
- Data Automation, Intelligent Document, Video, Image, and Audio Processing Part 2 (6:07)
- Data Automation, Intelligent Document, Video, Image, and Audio Processing Part 3 (5:45)
- Intelligent Prompt Routing with AWS Bedrock (10:38)
- Using LLMs in Batch Inference Mode in AWS Bedrock (12:26)
Building Low-Latency, Interruptible Voice Agents with AWS
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- Setting Up AWS Access Keys (8:35)
- Setting Up Files (2:31)
- Understanding Speech-to-Speech Models (2:46)
- Understanding Bidirectional Streaming (6:03)
- Creating Audio Configurations (3:24)
- Setting Up Debugging Functions (4:24)
- Non-Blocking Asyncio Python (5:11)
- Eventloop and Multithreads in Python (9:27)
- Getting Guests, Dynamodb Call (2:48)
- Getting Reservations, Dynamodb Call (7:28)
- Updating Reservations, Dynamodb Call (9:42)
- Event Templates Part 1 (7:30)
- Event Templates Part 2 (8:25)
- Exploring Tools Our Model Has Access To (6:26)
- Tool Result Event (1:37)
- Initialising the Bedrock Stream Manager Class (6:14)
- Initialising the Bedrock Stream (6:23)
- Sending Raw Events to Bedrock (2:28)
- Processing Audio Input (3:03)
- Sending Events to the Bedrock Stream (7:28)
- Processing Incoming Responses From Bedrock (7:10)
- Handling Tool Requests + Completions (3:51)
- Executing Tools + Gracious Closing and Shutting Down (2:50)
- Separate Input and Output Streams (4:14)
- Finishing the Audio Streamer Class (8:39)
- Ending the Stream Clarification (0:55)
- Finishing Up Our Final Script (3:06)
- AWS Quotas and Credentials (1:59)
- Installing Necessary Libraries (3:26)
- Setting up DynamoDB (5:01)
- First Test of Our Agent (4:46)
- Testing Reservation Updates (3:06)
- Testing with the Debug Flag (2:19)
- Testing the Final Product (7:03)
- Cleaning Up (2:10)
- Congratulations! (0:49)