Rahul Trisal

    Generative AI on AWS - Amazon Bedrock, RAG & Langchain[2026]

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    Generative AI · Online Course

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    This comprehensive course offers a deep dive into building production-ready Generative AI solutions on AWS, making it highly valuable for developers, cloud architects, and tech enthusiasts. Led by Rahul Trisal, the curriculum guides learners through the core concepts of Artificial Neural Networks and Foundation Models before transitioning into practical, hands-on implementations. Students will explore Amazon Bedrock in detail, mastering its architecture, pricing models, and inference parameters. The course stands out for its practical approach, guiding you through over seven real-world use cases. These include text summarization using the Cohere foundation model, conversational chatbots built with Bedrock Converse API and Langchain, and sophisticated Retrieval Augmented Generation (RAG) applications using Claude and FAISS. Additionally, learners will gain hands-on experience deploying serverless applications using AWS Lambda, API Gateway, and Amazon Bedrock Agents. Perfect for both beginners and experienced professionals, this course bridges the gap between theoretical AI concepts and scalable cloud deployments, ensuring you can confidently design and implement cutting-edge GenAI architectures on AWS. With a dedicated focus on the latest tools like Amazon Q Business, Amazon Q CLI, and Langchain, this learning journey equips you with the in-demand skills required to build autonomous agents and secure knowledge bases, making you highly competitive in the modern tech landscape.

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    Rahul Trisal

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    AI

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    Rahul Trisal is a dedicated cloud computing and artificial intelligence educator who specializes in bridging the gap between complex AWS architecture and practical, production-grade generative AI implementation. With a sharp focus on modern engineering paradigms, Rahul creates comprehensive technical curricula designed to empower developers to transition from theoretical understanding to hands-on deployment. His teaching philosophy centers on the integration of cutting-edge tools, such as Amazon Bedrock, LangChain, and CrewAI, into scalable workflows that solve real-world business challenges. By emphasizing architectural best practices, including the use of the AWS Cloud Development Kit (CDK), Rahul ensures his students do not just write…Show more

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    Program Overview

    Online Course

    Learning format

    Generative AI

    Subcategory

    $19.99 (list $9.99)

    Price

    Price may change · updated within 1–2 weeks

    English

    Course language

    What You'll Learn

    • Learn fundamentals about AI, Machine Learning and Artificial Neural Networks.
    • Learn how Generative AI works and deep dive into Foundation Models.
    • Amazon Bedrock – Detailed Console Walkthough, Bedrock Architecture, Pricing and Inference Parameters.
    • Use Case 1: Text Summarization for Manufacturing Industry using API Gateway, S3 and Cohere Foundation Model
    • Use Case 2 - Build a Chatbot using Bedrock Converse API - DeepSeek and Nova Pro Foundation Model, Langchain and Streamlit
    • Use Case 3- Employee HR Q & A App with Retrieval Augmented Generation (RAG) - Bedrock - Claude Foundation Model + Langchain + FAISS + Streamlit
    • Use Case 4 : Serverless e-Learning App using Bedrock Knowledge Base + Claude FM + AWS Lambda + API Gateway
    • Use Case 5 : Build a Retail Banking Agent using Amazon Bedrock Agents & Knowledge Bases
    • Use Case 6 - Build Infrastructure Coding Agent using Amazon Q CLI and AWS CloudFormation Server.
    • Use Case 7 : Amazon Q Business - Build a Marketing Manager App with Amazon Q
    • Python Basics Refresher
    • AWS Lambda and API Gateway Refresher

    Best For

    • Software developers looking to integrate Generative AI capabilities into enterprise cloud applications.
    • Cloud architects and AWS engineers aiming to master Amazon Bedrock for scalable AI deployments.
    • Data practitioners transitioning into LLM application development using Langchain and RAG patterns.
    • Technical professionals who want to build and deploy autonomous AI agents on serverless AWS infrastructure.

    Not For

    • Individuals without a basic understanding of Python programming or general AWS cloud concepts.
    • Data scientists seeking deep academic theory on machine learning mathematics or model training algorithms.
    • Professionals who strictly use non-AWS cloud platforms for their AI infrastructure.

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