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.

Are you anxious every time you deploy an AI agent? Based on experience with major domestic corporations and global big tech companies, we will show you how to systematically measure and improve agent quality using LangSmith.

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!

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

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!

Building 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.

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

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

Learn the entire process of running the latest Gemma 4 model directly on your MacBook without the burden of paid API costs. You will master performance maximization techniques using Apple Silicon's Metal API and optimal parameter settings for different VRAM capacities, while gaining the ability to build production-level local AI infrastructure based on FastAPI.

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

It's okay if you don't know a single line of code. We are now in the era of 'Vibe Coding,' where you develop by 'conversing' with AI.

A selfish era where only those who know how to properly utilize AI can generate profit. Essential web development concepts for profitability and a realistic guide you must know to 'properly' direct AI coding agents. From the mindset of coding without writing a single line of code to realistic methods for building a product with zero budget, and even practical details on business registration and tax processing. This is an AI-driven profitable web programming guide filled with insights gained from the actual field.

[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.

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.

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!

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

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.

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.

Deterministically control AI agents through a 5-layer harness architecture and 4 workflow layers, and immediately apply a scalable project structure to real-world practice. (Based on Claude Code, but the same principles apply to other AI tools.)

This is an advanced course focused on designing and implementing Multi-LLM architectures and orchestration-centered Agent systems (Main/Sub, Tool, Task Runtime, Agent Registry) by strategically combining GPT, Gemini, and LLaMA (local) based on Spring AI and Spring Boot. Moving beyond simple LLM calls, the curriculum covers the implementation of scalable, stable, and continuously improving AI systems. This involves applying Agentic Workflow Patterns (Chain, Parallel, Routing, Orchestrator–Workers, Evaluator–Optimizer) and Multi-Agent structures, separating execution layers like RAG and external APIs/DBs via Tool/ToolRegistry, and utilizing DAG engines, YAML declarative workflows, and Validated DSL (validation immediately after loading). Furthermore, the course includes Circuit Breakers, Reactive Streams, Redis monitoring, parallel processing, and iterative evaluation loops. It expands from Thymeleaf (SSR) exercises to decoupled Front-end/Back-end architectures using React and REST, while integrating tool and agent runtimes via MCP (Model Context Protocol) to build AI architecture design capabilities at a production-ready level. The ultimate goal is to evolve beyond being a simple AI user who merely integrates APIs and writes prompts, becoming a developer capable of designing AI systems—explaining and balancing Multi-LLM, agents, workflows, declarations, and validation within a single execution architecture.

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.

From a developer who only used ChatGPT to a developer who handles AI agents. Learn practical ways to maximize coding productivity using Codex's Rules, Hooks, Skills, and MCP.

Building an MVP with AI is no longer difficult. However, most projects stop at the next stage. 👉 You’ve built the features 👉 But development doesn't continue Why does this happen? The problem isn't the code; 👉 It's because there is no structure that allows AI to work continuously. --- In this course, based on an existing project, 👉 We will cover the process of building a structure 👉 That allows AI to continue development on its own. --- Instead of simply using AI tools, we will: * Create a docs structure * Define the SSOT (Single Source of Truth) * Execute development on a per-ticket basis * Connect QA and iteration cycles 👉 To complete a single "AI Development System." --- Through this process, you will: 👉 Create a structure where development continues 👉 Even without a human manually coding. In other words, you can: 👉 Build and understand a development system 👉 That operates AI like a team. --- This course is designed for: 👉 Those who want to build a structure applicable to their projects immediately 👉 Those who started development with AI but found it difficult to sustain 👉 Those who want to move to the next level after "Vibe Coding" --- Beyond just learning, we provide an experience where you: 👉 Take action 👉 Build a structure that actually works 👉 And walk away with a framework you can apply to your own projects.

This is a 4-session intensive course designed to transform Claude from a simple conversation tool into a business automation system. You will learn core concepts such as agents, Claude Code, and workflows through practical use cases, gaining the hands-on ability to build end-to-end automation systems in your own field—even without development knowledge. This powerful weapon is most effective in the hands of non-developers who possess tacit knowledge. On the other hand, if you are a developer, it is good to understand why. An AI tsunami is approaching. Do not be swept away; use this as your weapon.