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Claude Code: Build Enterprise RAG and Knowledge Graph Apps
New
Rating: 5.0 out of 5(1 rating)
16 students

Claude Code: Build Enterprise RAG and Knowledge Graph Apps

Build Enterprise AI with Claude Code, FastAPI, LangGraph, Hybrid RAG, Neo4j Knowledge Graph and Multi Agent AI
Created byAritra Basak
Last updated 7/2026
English

What you'll learn

  • Build a production ready Enterprise AI application using Claude Code with Spec Driven Development and real-world software engineering practices.
  • Design and implement Hybrid RAG pipelines using Vector Databases, document chunking, embeddings, and intelligent retrieval workflows.
  • Build and query Neo4j Knowledge Graphs, design ontologies, and implement Graph RAG for enterprise AI applications.
  • Develop Multi Agent AI workflows using LangGraph to orchestrate vector search, Knowledge Graph retrieval, and AI reasoning.
  • Implement document ETL pipelines to process PDF and CSV files for Vector Databases and Knowledge Graph ingestion.
  • Master Claude Code fundamentals, including Slash Commands, CLAUDE md file, Skills, and production ready implementation workflows.
  • Apply enterprise AI architecture, system design, testing, and debugging techniques to build scalable Agentic AI applications.

Course content

11 sections45 lectures6h 46m total length
  • Course Introduction & What You'll Build with Claude Code4:05
  • Installing and Setting Up Claude Code4:28
  • Claude vs Claude AI vs Claude Code: What's the Difference?1:07
  • Authenticating Claude Code with Your Claude Account1:15

Requirements

  • An active Claude Code subscription is required, as we'll use Claude Code throughout the course for AI assisted software development.
  • Access to OpenAI models (API or subscription) is recommended since we'll use both Claude and OpenAI models in different parts of the project.
  • A good understanding of Python programming is required. This course focuses on building enterprise AI applications rather than teaching Python fundamentals.
  • Basic knowledge of AI, Large Language Models (LLMs), and Retrieval Augmented Generation (RAG) is recommended to get the most out of the course.
  • No manual coding is required. We won't write application code by hand, instead, you'll learn how to build production ready software using Claude Code and Spec Driven Development.
  • A computer capable of running Python applications and installing the required development tools.

Description

Stop building toy AI chatbots. Learn how to build a production ready Enterprise AI application using Claude Code with real world software engineering practices.

In this course, you'll build a complete IT Service & Consulting Revenue Intelligence Platform from scratch. Instead of relying on vibe coding, you'll learn how professional engineering teams use spec-driven development, system architecture, and Claude Code to develop scalable AI applications.

This course is entirely project based. Every concept is taught while implementing a real enterprise application that combines Hybrid RAG, Knowledge Graphs, Multi Agent AI, LangGraph, Neo4j, Vector Databases, and Document ETL pipelines.

What You'll Build

You'll develop a complete Enterprise AI application capable of:

  • Uploading enterprise documents

  • Processing PDF and CSV files

  • Building a Hybrid RAG pipeline

  • Creating a Neo4j Knowledge Graph

  • Designing an ontology for Graph RAG

  • Implementing Multi Agent workflows using LangGraph

  • Retrieving information from both Vector Databases and Knowledge Graphs

  • Building a secure authentication system with JWT

  • Creating a modern chatbot interface

  • Developing production ready APIs

  • Testing the complete application from end to end

Why This Course Is Different

Most Claude Code courses focus on generating code snippets or building simple chatbots.

This course teaches you how to engineer a real AI product.

You'll learn:

  • Enterprise software architecture

  • Spec driven development

  • AI assisted software engineering

  • Production development workflows

  • Scalable system design

  • Building maintainable AI applications

Every feature is designed before implementation, just like in real software teams.

Who This Course Is For

This course is ideal for:

  • Software Engineers

  • AI Engineers

  • Backend Developers

  • Full Stack Developers

  • Solution Architects

  • LLM Application Developers

  • Anyone who wants to build production ready AI applications using Claude Code

After Completing This Course

You'll be able to design and build enterprise grade AI applications using Claude Code instead of relying on simple prompt-based coding. More importantly, you'll understand how to think like an AI engineer from requirements and architecture to implementation, testing, and deployment.

If you're ready to go beyond simple AI demos and build real world, production ready Agentic AI systems, this course is for you.

Who this course is for:

  • Software Engineers who want to build production ready Enterprise AI applications using Claude Code.
  • AI Engineers looking to master Agentic AI, Hybrid RAG, Knowledge Graphs, and Multi Agent workflows.
  • Python Developers who want to apply AI to real world enterprise projects instead of building simple chatbot demos.
  • Developers already using Claude Code who want to learn enterprise development workflows, Spec Driven Development, and AI assisted software engineering.
  • Solution Architects and Technical Leads who want to understand how to design scalable AI systems using LangGraph, Neo4j, and Hybrid RAG.
  • Anyone with Python and basic AI knowledge who wants to learn how real enterprise AI applications are designed, built, and tested from scratch.