LangGraphを活用したAI Agent開発（feat. MCP）

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

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.

This is a basic LangChain lecture that extracts the key points from official documents for the price of a cup of coffee. Get familiar with LangChain grammar before you start developing!

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

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!

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

Implementing a Retrieval-Augmented Generation (RAG) Intelligent AI Agent with LangGraph! From theory to practice, this is a hands-on tutorial that even beginners can easily follow.

This is a course that beginners can follow along with in a fun and easy way. Beyond simple chatbots, AI Agents that automate industry-specific business workflows. This course quickly covers the basic structure and core technologies of AI Agents (LangChain, LangGraph, RAG) in 1.5 hours, and is an introductory course where you build practical skills by directly creating mini agents that work with actual code. After completing the course, you'll understand the necessity of industry-specific data preprocessing and scalable design, and be prepared for advanced concepts covered in deeper courses.

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.

Claude + IntelliJ TodoList Development - Complete MCP Mastery Learn how MCP works perfectly by creating a TodoList with Claude and IntelliJ.

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

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

AI technologies are emerging with various new developments day by day. We need to study AI to keep up with them, but it's honestly not easy. This lecture will teach you about MCP (Model Context Protocol), a topic that has been receiving attention in AI recently. This lecture is targeted at people who are encountering MCP for the first time or those who work in fields other than development, such as design or planning, but are interested in MCP servers.

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.

We create an AI judge by combining CrewAI, facilitating LLM-based multi-agent technology, with knowledge graphs and inference systems.

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

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

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