How to build an advanced RAG router based assistant with Amazon Bedrock using LLMs, Embeddings model, and Knowledge Bases for Amazon Bedrock.
How to build a chat assistant with Amazon Bedrock using LLMs, Embeddings model, and Knowledge Bases for Amazon Bedrock.
How to build a simplified Corrective RAG assistant with Amazon Bedrock using LLMs, Embeddings model, Knowledge Bases for Amazon Bedrock, and Agents for Amazon Bedrock.
The course equips you with the skills to deploy Large Language Model (LLM)-based applications into production using serverless technology with Amazon Bedrock.
How to process semi-structured data using Large Language Models (LLMs) on Amazon Bedrock.
How to build a backup assistant using AI agents on Amazon Bedrock.
How to convert GPT text prompts to text prompts for Large Language Models (LLMs) on Amazon Bedrock.
How to use AI to build a content-based file tagging system using Amazon Bedrock.
This sample showcases how agents built on the Strands Agents framework understand natural language queries and intelligently select appropriate tools, connecting AWS SDKs with custom file utilities through a conversational interface providing developers a practical blueprint for building their own AI assistants.
A production-ready GenAI voice assistant that listens, understands, and responds in real time using AWS Transcribe, Amazon Bedrock (LLMs), and AWS Polly — fully deployed and cost-controlled.
Prepare for the AIP-C01 exam – AWS Certified Generative AI Developer (Professional) 2026 with practice questions and real-world scenarios.
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