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

From the core concepts and infrastructure setup of Kafka, Hadoop, Spark, and Airflow to hands-on practice with Java and Python, as well as building production-level pipelines in an AWS environment.

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

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 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.

You can learn about Text-to-SQL systems that generate and query SQL statements in real time in response to user questions.

Learn about configuring an MSA server using Spring Cloud.

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 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.

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

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.

You can learn about Text-to-SQL systems that generate and query SQL statements in real time in response to user questions.

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

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.

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.

Have you wanted to implement RAG but felt overwhelmed by connecting everything from embeddings to vector storage and search? Based on real-world service development experience, this course explains the core concepts of pgvector and the service source code. By calling the API directly, you can quickly understand the entire flow of how RAG vector search works.

"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.

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

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

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.

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

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.

"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!

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.

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

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

Done in a single line of command. Hermes, the AI agent that remembers, automates, and grows on its own. Even if you are not a developer, you can become someone who 'delegates' work to AI starting today. SMARTFORK will be with you from installation to practical application.

[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.