The 10x AI-Native Developer: How to Achieve Overwhelming Performance with AI at Work

With step-by-step explanations that even beginners can easily understand, the once-vague coding tests will become clear. Learn only what you need and apply it to real-world practice right away!

No coding skills? No problem! Turn your ideas into real profit in just 4 weeks. Use AI and the latest tools to build a website and an app simultaneously and launch your service right away.

I aim to help you understand the core concepts of Python within 60 minutes! I focused on the "Why" and "When" to use them, rather than just blind syntax.

In a world where every resume looks the same, "differentiation" is what gets you hired. Over the course of 6 weeks, learn 4 practical resume strategies delivered directly by an active backend professional.

Beyond simply copy-pasting with AI, you will learn how to actually automate repetitive tasks for non-developer professionals by connecting Claude Chat, Cowork, MCP, n8n, Supabase, and Vercel. Set against the backdrop of a virtual company called DingcoLabs, you will follow hands-on scenarios for PM, Marketing, Sales, CS, and HR to build work automation systems that can be applied to your company immediately.

"I have a backend technical interview in a week—where should I start?" The secret to answers that make interviewers nod in approval. Fully master the actual answer patterns of successful candidates from Naver, Kakao, Coupang, and Toss in just 3 days!

We live in an era where AI can generate 10 files at once. However, if you can't track where the code changed, if it conflicts with your teammates' work, or if you don't know how to revert it—your productivity will suffer no matter how well you use AI. This course isn't just a list of commands like git add and git commit. It provides a visual understanding of the principles behind safely managing AI-generated code and merging it with your team's work. In just two hours, you will transform into a developer who can freely track, revert, and merge any code, whether it was created by AI or written by yourself.

You've probably written SQL using JdbcTemplate before, right? Everyone has likely had that experience of sighing while having to fix both the SQL and the RowMapper every time a single column changes. This course starts from that very pain. Doing a single SELECT with pure JDBC takes 35 lines. You open a Connection, create a PreparedStatement, iterate through the ResultSet, and if you miss a single close(), the server crashes. After typing through this hell yourself, when you finally encounter a single line of JPA's save(), you'll feel "this is why we use JPA" not just in your head, but in your hands.

If you ask an AI to "get the top 10 sales," it will whip up a plausible-looking query in no time. However, to determine if that query is actually correct, if the results of joining three tables are accurate, or if it's performing a full scan on 500,000 records without an index—you ultimately need a foundation in DB basics. This course doesn't cover anything overly difficult. In just 2 hours, you will learn the entire flow of SQL by coding along, covering exactly what you need to know before giving instructions to an AI. By the end of this lecture, you will no longer feel uneasy when faced with a query generated by AI.

This is an introductory backend development course where you learn through understanding rather than memorization, and experience rather than theory. Instead of reciting a Googled definition when asked "What is JPA?" in an interview, this course will empower you to give an answer based on experience, starting with "Well, I've been through JdbcTemplate hell..." You will gain a deep, intuitive understanding of "why we use frameworks" by experiencing firsthand how 30 lines of pure Java ServerSocket code shrink down to just 7 lines in Spring Boot. After 6 sessions, you will walk away with a functional portfolio piece: a Todo List REST API built with Spring Boot + JPA.

The lecture explains why the harness is more important than the model through the Claude Code architecture. It covers how to design the Claude Code task system using six structures: Context Harness, Permission Harness, Verification Harness, Tool Harness, Subagent & Worktree Harness, and Debugging Harness. Afterward, it connects these concepts to CLAUDE.md, session management, large codebase control, worktree parallel operations, error log analysis, and tracking environment variables and configuration scope issues, establishing the standards for continuously using Claude Code in practical backend and DevOps workflows.

There's so much talk about AX these days. At Selfish Club, we started asking ourselves, "How 'agentic' can our way of working actually become?" So, for two months, we just dove right in. From how we drew the roadmap and what our non-developer crew members built with Claude, to how we transformed the process of creating product detail pages—which we used to build from scratch every time—into a system. Instead of a polished conclusion, we're sharing the raw, chaotic process of our trial and error.

Master Claude Code from the basics to a professional level. You will learn core features (CLAUDE.md, sub-agents, MCP, Hooks, etc.) to develop and deploy actual services, concluding with foundational appendices for non-majors and advanced application lectures.

In the era of AI and Big Data, are you utilizing your organization's data effectively? This course builds essential capabilities for reading and interpreting data, covering everything from the foundations of statistical thinking to the core principles of machine learning and deep learning. Grow into a practical leader capable of discovering patterns amidst volatility and making data-driven decisions.

: "From Mathematical Foundations to the Latest Models, Completing the Deep Learning Pipeline with PyTorch (44 Lectures in Total)" The era of simply learning how to call model.fit() is over. From the very basics of artificial neural networks—differentiation and gradient descent—to essential PyTorch techniques used in the industry, and CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and step into the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.

It's okay if AI feels unfamiliar and difficult to you. In just one week, I will share the entire "trial and error" journey of building everything from a membership landing page to automation and data analysis from scratch using Claude Code. Even if you don't know how to code or are a complete AI beginner, I'll show you through real-world examples so you can take on the challenge yourself.

From PC control to high-level research and app development A guide to building your own 'AI Work Assistant' ready for immediate real-world deployment

This is a practical project course where you will build a complete web service from planning to deployment using AI coding tools. You will gain hands-on experience with the entire process—including database design, file storage implementation, and service operation—within a Windows environment to acquire practical development skills for the AI era.

This is an advanced course focused on designing and implementing Multi-LLM architectures and orchestration-centered Agent systems (Main/Sub, Tool, Task Runtime, Agent Registry) by strategically combining GPT, Gemini, and LLaMA (local) based on Spring AI and Spring Boot. Moving beyond simple LLM calls, the curriculum covers the implementation of scalable, stable, and continuously improving AI systems. This involves applying Agentic Workflow Patterns (Chain, Parallel, Routing, Orchestrator–Workers, Evaluator–Optimizer) and Multi-Agent structures, separating execution layers like RAG and external APIs/DBs via Tool/ToolRegistry, and utilizing DAG engines, YAML declarative workflows, and Validated DSL (validation immediately after loading). Furthermore, the course includes Circuit Breakers, Reactive Streams, Redis monitoring, parallel processing, and iterative evaluation loops. It expands from Thymeleaf (SSR) exercises to decoupled Front-end/Back-end architectures using React and REST, while integrating tool and agent runtimes via MCP (Model Context Protocol) to build AI architecture design capabilities at a production-ready level. The ultimate goal is to evolve beyond being a simple AI user who merely integrates APIs and writes prompts, becoming a developer capable of designing AI systems—explaining and balancing Multi-LLM, agents, workflows, declarations, and validation within a single execution architecture.

Learn Springboot + Flutter RestAPI Board Creation Faster Than Anyone Develop a CRUD server with Springboot and create your own board with Flutter!!

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

This course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.

This is a 'Spring Batch' course that can be used immediately in practice, designed for job seekers and working developers who are new to Spring Batch!

Can you create a service with your ideas even if you don't know how to code? With AI, it is possible! In this course, you will experience the entire process of turning an idea into a real web service using "Vibe Coding" tools used in the industry, such as Gemini, Lovable, Antigravity, Cursor, and Claude Code. You won't just learn how to use the tools; you will master a new way of service development in the AI era—from planning and deploying to integrating payments. Point 1. Master 5 Core Vibe Coding Tools - Hands-on practice with core features and applications of Gemini, Lovable, Antigravity, Cursor, and Claude Code - Understanding the Vibe Coding development method of collaborating with AI Point 2. Building a Real Service Without Coding - Hands-on process of planning and implementing a book recommendation web service - Understanding the entire service creation flow: Idea → Development → Deployment Point 3. Practical Skills for Service Launch and Operation - Understanding domain purchase, server setup, and the deployment process - Learning core operational technologies such as payment module integration and SEO settings

This is a full-stack hands-on course where you will implement a ChatGPT clone from scratch. From Spring Boot server to React frontend | Neo + Essential This is not just a course where you simply follow along with the code; it guides you through actual service deployment so you can build a high-quality AI chatbot service.

1. Python coding study to obtain the AI certification, AICE Associate 2. Step-by-step Python coding study from basics to applications 3. Lectures by Professor Joongheon Kim of Korea University, a scholar in the field of AI

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.

Building a TodoList with Claude + IntelliJ - Complete MCP Mastery Master the workings of MCP by creating a TodoList with Claude and IntelliJ!

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!

[Up-to-Date Knowledge for Current Times] 1. Changes brought by AX, ChatGPT, and robot technology. 2. Commonalities of Blockbuster-Kodak Film-Nokia. 3. Five Current AX Keywords. - OOOO coin to maintain dollar hegemony. - Musk's OOOO to cut government operating costs. - Trump's OOOO strategic reserve. - China's OO kindergarten, OO receiving private education. - China's OO factory, with no workers, OO is no longer needed. 4. ChatGPT/Gemini/Grok - Write prompts based on previously learned content and compare results - Generate images with Claymotion infographics