First Steps in System Design with LLM: Designing Operational AI Service (RAG·AI Agent) Architectures

Beyond the basics of API design, CRUD implementation, and JWT authentication, all the way to backend architecture design! This is an introductory system design course to help you create 'your own backend architecture' so you can confidently discuss design experience in interviews.

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.

This course covers the entire process of evolving ChatGPT from a simple conversational AI into an intelligent AI Agent that performs real-world tasks. By utilizing the three core frameworks—LangChain, LangGraph, and LangSmith—you will build AI Agents that can be used immediately in practice.

What if AI could directly open a browser and write shell scripts to resolve server issues? Through practical automation know-how implemented with OpenClaw across Windows and Linux, we guide you on the shortest path to completing your own powerful remote development environment without complex configurations.

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.

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.

This is a Silicon Valley internship and 30 Big Tech system design & open-source contribution mastery course that ensures job security even in the AI era. In this course, you will design and scale 30 real-world system designs using cases from Big Tech companies such as Netflix, Tesla, Meta, and Tinder. Finally, you will design your own service from architecture to DB and scaling.

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.

Beyond a chatbot that simply generates answers, you will directly implement an autonomous AI Agent that makes its own judgments, calls tools, and performs multi-step tasks. You will learn through step-by-step practice, covering everything from OpenAI Agents SDK's Tool Calling, Handoff, Guardrail, Session, and Tracing to connecting external tools and databases using MCP, as well as LangChain and Deep Agents' Planning, Subagents, Filesystem, and Memory. The ultimate goal is to equip you with the ability to design and implement tool-integrated AI Agents that can be applied to real-world tasks.

Beyond the basics of API design, CRUD implementation, and JWT authentication, all the way to backend architecture design! This is an introductory system design course to help you create 'your own backend architecture' so you can confidently discuss design experience in interviews.

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.

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

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.

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

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

In an era where AI writes code for you, will you remain a 'Coder' or leap forward to become an 'Architect'? This course is designed for junior developers who can handle basic implementation but feel stuck about the next steps or are anxious about falling into the trap of 'fake experience'. We aim to go beyond simply learning clean architecture theory and turn Robert C. Martin's (Uncle Bob) high-level design principles into weapons for the AI era.

Mastering difficult AI with just one single analogy?! A first step into AI principles, understanding through core concepts rather than just terminology.

The limitations of LLMs? I’ll share practical solutions to real-world problems based on RAG trial and error and operational know-how from working in Silicon Valley.

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.

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.