RAG System Implemented with AI Agents (w. LangGraph)

This is a basic Python course for non-major beginners. Theory textbooks are provided through Wikidocs, and practice materials are provided through Github.

Neo4J-based Knowledge Graph RAG System: Next-Generation Search Technology That Goes Beyond Simple Vector Search to Leverage Data Relationships Maximizing RAG Performance with the Power of Graph Databases!

This lecture covers RAG (Retrieval-Augmented Generation) system fundamentals and implementation using LangChain. Participants will understand RAG's core principles and learn to build and evaluate systems using LangChain.

Learn LangChain's basic concepts and usage with Python. Hands-on practice will be conducted primarily in a Google Colab (colab) environment, with materials provided via Github.

This course is designed for beginners and consists of easy explanations and various hands-on projects. It covers data collection using web crawling and LangChain tools, and summarization, extraction, sentiment analysis, and recommendation systems using LLM.

Create your own AI chatbot using Python's basic syntax and libraries. Learn through a step-by-step process of completing 5 projects, including PDF document-based RAG, and deploy them as web services.

Neo4J-based Knowledge Graph RAG System: Next-Generation Search Technology That Goes Beyond Simple Vector Search to Leverage Data Relationships Maximizing RAG Performance with the Power of Graph Databases!

LangGraph, packed with a major corporation's AI Agent lead's know-how. We deliver knowledge gained from real-world challenges.

We explore how to create an AI judge by combining knowledge graphs, reasoning systems, and various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology.

AI proficiency determines your salary. Leave those tedious repetitive tasks to AI 'Almost Everything About Work Automation' teaches you how to create automation systems that handle your work with just a few clicks, no coding knowledge required. You'll be freed from boring document work and data organization, and transform into an 'AI work expert' who stays ahead of others.

The Latest Trend in Generative AI, AI Agents! How to Stay Ahead with Cursor, which handles all development tasks, and MCP, which expands functionality!

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

Develop various features using Spring WebFlux. This course will teach you WebFlux's essential concepts and practical implementation.

We're building an AI-powered video conferencing application with real-time AI agents, meeting summary features, and post-call functionality.

This is a hands-on tutorial on how to integrate with IntelliJ and develop quickly using the Model Context Protocol (MCP).

LLM: A pro quickly delivers core content, from essentials to practical tips!

If you want to create your own AI service without coding, this course is the perfect solution. Using the Dify no-code platform, you can create high-quality AI apps with just your ideas. Instead of complex theory, it's structured around hands-on projects, allowing both AI beginners and working professionals to develop practical skills.

This course covers the entire process of designing and implementing generative AI services centered on LangChain 1.0 and LangGraph through step-by-step hands-on practice. Beyond simple LLM calls, you'll directly implement operational AI system architectures that include agent-based architecture, state management, memory, streaming, middleware, and Human-in-the-Loop. Through hands-on practice with document/PDF/web data-based RAG systems, SQL Agent (Chinook DB), tool-calling-based Agents, Supervisor pattern multi-agents, and state machine-based workflows using LangGraph Graph API, you'll build reusable agent pipelines that can be immediately applied in real-world scenarios. Additionally, through structured output (Pydantic-based), agent middleware (Summarization, HITL, Retry, PII protection), and token/step-by-step streaming, you'll complete generative AI applications with the stability, scalability, and controllability required in actual services. 👉 For those who want to accurately understand the internal structure and execution flow of LangChain/LangGraph 👉 For those who want to implement RAG·Agent as a real service structure, not just a "demo" 👉 This is the optimal course for those who need a realistic practical roadmap covering state-based agents, SQL·document automation, and multi-agent orchestration.

AI writes on my Slack and Notion for me? Work smarter with MCP that surpasses the limitations of existing AI!

This course focuses on M365 Copilot, a smart work partner in the Microsoft 365 ecosystem, and covers how to achieve work innovation by utilizing AI in an environment where security and copyright are protected. It introduces the main features of Copilot and various ways to leverage it in conjunction with Microsoft 365 services, while also presenting prompting techniques to elicit accurate and effective responses.

No coding knowledge required. Build it instantly in your browser with Google's latest tool (IDX)—no installation needed! Stop studying coding syntax! This is a high-speed practical course where you'll build an RAG chatbot that perfectly understands internal documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

Do you still code directly these days? Now is the era where even vibe coding is too much hassle! Become an AI automation expert with n8n without coding. A practical automation workflow design guide you can apply immediately at work Action-oriented automation strategies that maximize work efficiency. Build intuitive workflows with n8n and experience workplace innovation

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

Learn the easiest way to handle AI with Spring AI. Let's learn Spring AI by building a RAG chatbot.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is the technology that has come closest to AGI at this point in time. In this lecture, we explore LLM and Agent technologies from a general public perspective.