Solving Claude Code All at Once for Beginners - A Lecture by the Author of Claude Code Master

This is a career guide course that covers the entire process of landing a developer job or switching careers, including resumes, portfolios, technical interviews, and behavioral interviews. The theory section outlines the process of finding the right company for you, analyzing job postings, and preparing for interviews and coding tests.

This course allows you to experience a comprehensive list of questions and answer strategies for both technical and behavioral interviews. In particular, the curriculum is designed to help you prepare for interviews by learning—through Q&A—server scaling strategies and large-scale data processing strategies essential for junior-level technical interviews, as well as how to provide the best answers to open-ended questions typically encountered in final interviews.

This is a partial lecture from the theory section of a comprehensive career guide course that covers everything you need to prepare for developer job hunting and career transitions, including resumes, portfolios, technical interviews, and personality interviews. The theory section covers the process of finding companies that fit you, analyzing job postings, preparing for interviews and coding tests, and everything you need to know to prepare your resume and portfolio.

Learn how to utilize RabbitMQ to implement asynchronous architecture—the most fundamental method for processing large-scale data—through a tutorial format designed for easy understanding from basics to advanced applications based on Spring Boot 3.3. Learning materials (Notion links and Git Branch URLs) are provided for each lecture chapter. Please be sure to check the class notes.

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.

This will be the definitive guide to Claude Code. This course dives deep into how and why Claude Code works, teaches you how to directly apply the components of harness engineering, and even dissects actual production code. Take the know-how of a developer with over 10 years of experience and transform into a key talent in the era of AI agents.

Are you feeling stuck trying to implement an agent that goes beyond a simple chatbot? Based on my own trial and error and know-how from official documentation, I will show you how to build intermediate-level agents that can be immediately applied to real-world tasks.

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.

Now, your AI is no longer in the cloud. It runs directly inside your laptop. Using LM Studio and Ollama, we will show you how to build a Private AI environment that runs entirely locally— from data processing and document analysis to code generation. Without security concerns, without costs, and even faster— Move beyond simply "using" AI and start "truly mastering" it.

Build a Kiwoom Securities API-based automated stock trading system from scratch using the core features of Claude Code (MCP, Agents, Skills). It's perfectly fine for beginners. Get started with Claude Code right now!

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.

If you follow OpenClaw Parts 1 and 2, you eventually end up making a single agent do everything. As you do this, there comes a moment when prompts get tangled, memory gets mixed up, folders get messy, and you feel stuck, not knowing how to organize things anymore. This lecture is the "Introduction to Multi-Agents (Part 2.5)," designed to help you move one step further from that point. While maintaining a single bot, we will separate roles into two agents—planner and editor—and connect each agent to different workspaces and Telegram forum topics. You will personally build a structure where "different agents respond depending on which room you speak in." By following the hands-on practice, you will have the following in your environment: - A configuration file defining two agents: `content_planner` and `content_editor`, - A content folder structure where planning and drafting are separated, - A Telegram group chat where different agents are attached to specific forum topics, - And one actual draft of an Inflearn course introduction created through the collaboration of the two agents. In short, this is a practical class that helps you design the first step of upgrading your Telegram bot from a "single AI assistant" into a "small AI team with divided roles."

AI agents seemed vague, didn't they? We pass on problem-solving know-how from practical experience, covering everything from prompts to loops and graph engineering systems.

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.

From coding basics to running your own web service all at once?! Web Build All-in-One, connecting fundamentals and practical application.

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.

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.

Vibe coding is fast, but it's so fast that it's easy to skip over the foundations. For those who want to understand 'why it works' when looking at AI-generated code — we highlight the 8 core essentials (Terminal, Web, Deployment, Version Control, DB, Authentication, etc.) needed for steady vibe coding and the order in which to learn them. Even if it's your day 0 of coding, you can follow along!

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.

Your colleagues are already using Claude Code for their work—are you still doing everything manually? Don't worry! This course will turn you into a vibe coding master.

Which AI tool should I learn first? Stop worrying now! - Rated 4.8 by 80 students ⭐️⭐️⭐️⭐️⭐️ - ChatGPT, Claude, Gemini, Genspark, NotebookLM, Gamma, Skywork, Manus, Antigravity, Claude Code, MiriCanvas, Opal, CapCut, and more - Learn the core features of over 15 tools very easily over 20 days. - Through weekly assignments, we provide a course you can "internalize" rather than just "passively listen to." - All-in-one coverage: Prompt Engineering > Image Generation > PPT & Video Creation > Vibe Coding - 4 hours of lecture videos + weekly study materials + assignment certification system

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

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.

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.