LangChain Fundamentals in One Hour

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

LangGraph, packed with the know-how of an AI Agent lead from a major corporation. I will pass on the knowledge I've gained through trial and error in the field.

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.

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.

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!

This course is a practice-oriented program that goes beyond simple chatbots to build multi-agent systems where multiple agents collaborate. 👉 You will learn three frameworks—Swarm, LangGraph, and DeepAgents—step-by-step, completing six practical projects including a customer support chatbot, blog content creation, a PostgreSQL query agent, and an autonomous research agent. 👉 By implementing enterprise-grade features such as long-term memory using Redis and PostgreSQL, Human-in-the-loop security mechanisms, and cost monitoring, you will be able to build production-level systems that can be applied to real-world services immediately after the course.

Create a multi-agent system app with Agent Builder and Chatkit, and deploy the app with Cloudflare. All the latest technologies including GPT-5, Agent Builder, Chatkit, MCP, Fine Tuning, CoT have been incorporated.

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.

This is a tutorial-style Claude Code development course that beginners and those new to development can easily follow. Based on experience teaching planners, designers, and non-developers in offline classes, the course covers everything in one continuous flow—from beginner examples not covered in books to intermediate development examples. Using Claude Code, you will experience the step-by-step development process, starting with Hello World and progressing to a lucky draw, a device-optimized café menu management web page integrating Claude Design with Excel data, and a SaaS web application that can be connected to a database and deployed to cloud services. Tutorials are provided at each stage—theory, practice, and projects. Through hands-on exercises across 6 levels, you will learn AI-collaborative development methodologies and experience the entire development cycle, including cloud deployment and operations.

With v0, cursor AI, and various LLMs, from PRD to AI product recommendations! Complete your Next.js shopping mall through a practical project.

The most definitive practical guide for developers who want to integrate AI into their Spring projects right away! Beyond simple LLM API calls, you will perfectly master building production-level AI environments that can be immediately applied to real business logic using RAG and MCP.

From AWS EC2 backend operations to automatic error fixing, we are revealing the entire development process of Sidabari (https://github.com/cx8537/sidabari), a Claude Code-based automation tool. In this course, we provide all the actual prompts and conversation history used as learning materials, allowing you to experience the entire prompt input process involved in its creation.

This is a practice-oriented course for experienced developers with a computer science background transitioning to the latest AI technology stack. From the design to the implementation of LLM-based applications, you will establish AI solution adoption strategies by leveraging existing software engineering knowledge. Rebuild your career by integrating traditional development experience with modern AI technology.

Throw away those simple services you can make with vibe coding in just 10 minutes! You can learn 'real' practical vibe coding. Let's create advanced services at the level of actual services according to planning and design with Cursor AI NCOP. No Code, Only Prompt

This is a process of developing a practical web service in collaboration with AI agents based on TARS prompt engineering principles. You will gain full-stack development experience covering everything from UI/UX component creation to CRUD functions, API integration, and data visualization, ultimately completing your own idea as a viable MVP.

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.

[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.

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.

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

Explore how LLM applications are shifting the development paradigm. Understand why LLMs are becoming a sustainable core technology through comparisons with existing technologies, and learn about the essential skills and mindset shifts required for developers. Gain insights from expert instructors to grasp the essence and future direction of LLM application development.

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 practical Vibe Coding course where you will create a Travel MBTI diagnosis web app using only AI prompts and complete it to a production-ready level by actually integrating the Korea Tourism Organization's public Open API. You will learn how to transform crude results into a high-quality web app using prompt-splitting techniques, and cover the entire process from API key security to deployment.

"How is a 1-trillion parameter model trained?" Discover the scaling strategy of Kimi K2.5, revealed directly on stage by Moonshot AI at GTC 2026, in Korean on Inflearn. 2x token efficiency · 1 million token context · 1,000 agent swarm The next step for open-source LLMs is here. * This lecture is released for free through an official collaboration between Moonshot AI, the creator of Kimi, and Inflearn.

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!

You will experience the process of building an actual web service by combining various AI models such as Kimi, OpenCode, and Codex according to the situation. Beyond simple prompt input, you will learn practical development workflows for collaborating with AI, from requirement definition to code review and service completion, through hands-on practice.