Developing LLM Applications Using RAG (feat. LangChain)

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

Artificial Intelligence, AI, agents... They might seem grand, but once you try them, they're not as difficult as you think. That's why it's important to implement simple features yourself. Through practical projects that can actually be used at a company, you'll directly experience various use cases and learn how to utilize and apply AI agents.

A basic LangChain course that extracts only the essentials from the official documentation, all for the price of a cup of coffee(?). Get familiar with LangChain syntax before diving into full-scale development!

How to Use Storybooks A to Z. We show you everything about storybooks.

New to Flutter? A Flutter Contributor will guide you step-by-step! Start Flutter dev with an AI project using Gemini.

This is for those who want to deploy/operate services with AWS. From domain settings to Docker and serverless!

Test code! For those who are at a loss as to where to start, here it is. From writing tests to deploying through automation, all in one place!

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

A Complete Guide to Building an AI Chatbot System with Langchain and RAG! Provides a systematic learning process for generative AI development technology.

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

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.

By utilizing the operating principles and development tools of Microsoft 365 Copilot agents, you can systematically learn how to design and expand agents that operate in the way you desire. Chapter 1 organizes the essential concepts and principles to know before creating an agent, Chapter 2 explores agent types and tools suitable for various scenarios, and Chapter 3 allows you to directly implement your own agent using Agent Builder, SharePoint Agent, and Copilot Studio. From basics to hands-on practice, this single course will enable you to connect the potential of Copilot agents to practical applications!

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

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

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.

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.

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.

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

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.

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.

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