AI Agent Development Using LangGraph (feat. MCP)

RAG. Learn from Silicon Valley GenAI Hackathon Winner. Packed with real-world know-how.

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!

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.

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!

RAG. Learn from Silicon Valley GenAI Hackathon Winner. Packed with real-world know-how.

I'm learning how to build practical AI agents using LangGraph while working on various AI agent implementation projects using LangGraph.

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.

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

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

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

Innovation in Work Efficiency and Creativity – Agentic AI AI is now evolving beyond simple automation into a new stage where it can judge and execute on its own. Agentic AI is at the center of this change, serving as a core technology that helps businesses and organizations operate smarter. In this course, we have organized the content clearly and simply so you can understand how Agentic AI connects decision-making with execution and how it can be applied to practical work. Discover the essential knowledge for every professional preparing for the future right now.

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

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

Obsidian is not just a simple note-taking app, but a powerful Second Brain tool that allows you to systematically connect knowledge and information for long-term use. However, many users often give up midway due to the difficulties of initial setup, the complexity of utilizing plugins, and disorganized note structures. This course is designed to directly solve these problems. Based on the instructor's experience in building knowledge management, project management, learning records, and productivity automation using Obsidian, this course provides step-by-step guidance on where to start, how to structure your system, and which features to use when. Starting from basic installation and settings, you will understand metadata, frontmatter, and Markdown structures. You will learn through practical examples of daily, weekly, and monthly note systems, template automation, and core plugins such as Tasks, Dataview, and QuickAdd. Furthermore, the course covers Zettelkasten-style note linking, project management, voice memo automation, and integration with external services, allowing students to apply these techniques immediately to their own environments. Through this course, students will integrate scattered information into a single system and complete their own Second Brain that can be continuously utilized across learning, work, and projects.

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.

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

Building a TodoList with Claude + IntelliJ - Complete MCP Mastery Master the workings of MCP by creating a TodoList with Claude and IntelliJ!

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

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

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!

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.

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.