Everything about AI Agent Development Learned by Building a Chatbot (FastAPI, RAG, Vector, LangChain, sLLM/Fine-tuning)

You will learn about the overall DevOps process, including domain purchasing, deploying Spring Boot production servers using EKS, Docker basics, Kubernetes basics, AWS basics, CI/CD automation via GitHub Actions, ArgoCD, and Prometheus/Grafana.

Learn the basic, essential, and practical knowledge of Kafka that software developers need to know. We will integrate Kafka using Spring Boot and conduct hands-on exercises for sending and receiving messages tailored to various real-world scenarios.

Learn the basic data structures of REDIS and examples of practical use of REDIS through redis-cli (command) practice.

Implement Kakao and Google login using Spring Boot. JWT token-based login will be implemented. A simple interface will be constructed using Vue 3.

We develop a chat service using web socket/stomp and springboot. We also configure a simple screen using vue.js, which is a relatively easy framework. We also configure multi-server scalability design using redis pub/sub.

You will learn everything from the basic knowledge of Git/GitHub to practical solutions and strategies for various conflict situations encountered in the field.

Learn essential Linux knowledge that every developer should know, even if they're not a DevOps or Linux expert. The class will be hands-on and practice-oriented.

Learn about configuring an MSA server using Spring Cloud.

Learn everything you need to know about MariaDB (MySQL) as a developer, including beginners, backend developers, and SQLD exam preparation students. The class is focused on hands-on practice, where you will build your own DB.

Learn everything you need to know about MariaDB (MySQL) as a developer, including beginners, backend developers, and SQLD exam preparation students. The class is focused on hands-on practice, where you will build your own DB.

This course is a practice-oriented lecture that goes beyond 👉 just explaining the concepts of RAG (Retrieval-Augmented Generation), 👉 to building the actual working architecture yourself, 👉 and experiencing expansion and optimization. Starting from simple RAG examples, you will learn step-by-step—from Advanced RAG to Modular RAG and Agent-based RAG—at a level that can be immediately applied in the field.

Building an 'Intelligent Collaboration' Expert Agent Team Using Spring AI Router Pattern + RAG + MCP Beyond a Single Agent to Architecture: The Standard for Router Patterns and Agent Isolation Design

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.

Master the complete lifecycle of building modern Generative AI applications using Large Language Models, Retrieval-Augmented Generation, and Agentic AI systems. Learn to design enterprise-grade AI solutions from prompt engineering to deployment, combining LLMs with vector databases and external knowledge sources for production-ready applications.

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.

This course teaches you how to build AI agents from scratch to a production-ready level using OpenClaw. Beyond a simple introduction to features, you will master OpenAI, local LLMs, memory, sessions, Tools, and Skills in a single, cohesive workflow. Based on hands-on experience and know-how gained from developing AI and large-scale systems in Silicon Valley, the course explains architectures and operational methods applicable to real-world projects. By the end of the course, you will be able to design your own AI agents and implement automation by integrating them with various services. This is a practice-oriented course for those who want to go beyond just using AI and learn how to build and operate it themselves.

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.

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.

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!

[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.

Do you still code manually these days? We are now in an era where even "vibe coding" feels like a chore! Become an AI automation expert with n8n, no coding required. A guide to designing automation workflows that can be applied immediately to real-world tasks. Practical automation strategies to maximize work efficiency. Build intuitive workflows with n8n and experience a revolution in the way you work.

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

This is a lecture covering LLM theory and practical examples based on <Large Language Models, Just the Essentials!> (Insight, 2025).

You use ChatGPT, but haven't you found it difficult to explain why it gives certain answers? "I know terms like RAG, Agents, and Fine-tuning... but it's hard to explain them accurately." "I get tongue-tied whenever I hear LLM-related terminology." "Conceptual explanations are always vague during AI meetings." This course was created specifically for people like you. This is a theoretical course designed to help you understand LLMs not just as a 'tool,' but as a 'structure.' It doesn't teach you how to use ChatGPT or Gemini; instead, it establishes the foundation so you can explain exactly why they work the way they do.

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

You can enhance your development capabilities by deeply exploring the fundamental principles of large language models like ChatGPT and Claude. You will be able to learn a variety of information and development techniques that are not commonly encountered.

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.

"Your first step to creating a customized LLM with LoRA-based lightweight fine-tuning!" This is an introductory hands-on course designed so that even those new to LLMs can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading the model → applying data → training → comparing results. In a short time, you'll directly experience the workflow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, and gain an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

We will explore the types of applications and web services that can be built using LLMs.