Computational Thinking (Part 1) - Problem Solving Through Software

Along with reading, writing, and arithmetic, computational thinking is a skill that everyone living in the AI era must possess. Computational thinking can be simply defined as thinking like a programmer or a computer scientist. This course faithfully reproduces an actual university semester-long course and covers essential content for people encountering programming for the first time or beginners planning to major in computer science. Through this course, people without a background in computer science or with a humanities background can also develop the ability to communicate easily with professional programmers. Even in an era when learning prompts for AI vibe coding is necessary, this course helps you develop the ability to give AI more accurate and effective instructions through computational thinking.

Are you a non-major who doesn't know how to start learning C language? Did you learn C language as a major in school, but still can't write code? What's the point of studying C language for a long time? When you can't even create a single line of code properly... I'll pass on the know-how so you can program yourself. In this course, together with an experienced senior developer, you'll gradually learn C language grammar and application methods, and I'll guide you to a level where you can work on simple projects.

This course covers the latest data structures and algorithms used in representative open sources such as Linux.

It helps train the "constructive thinking" needed to frame problems.

Software quality is a habit! This course will teach you how to become the best programmer that companies want.

This course is for job seekers and career-changing backend developers preparing for coding tests with JAVA. We clearly identify question types by analyzing 195 actual past exam questions.

Slowly study the C language, which includes the basics of program development that developers need to know.

Learn the principles of Diablo 1-style PCG dungeon generation by implementing its structure in the console, with the theme 'Technology Supporting Game Development in the AI Era'. Expand this to 3D in Unity to complete a generation pipeline equipped with seed-based dungeon generation, mesh placement rules, and debug tooling. Through sample code and hands-on practice, connect to AI-assisted art production workflows, enabling you to create immediately applicable dungeon crawler prototypes.

This is a course where you can learn UML and object-oriented design even without programming experience. Concepts are explained through everyday examples (cafes, libraries, shopping malls), and you'll learn 9 types of UML diagrams step by step. You'll develop design skills that can be immediately applied in practice using theory and PlantUML.

A comprehensive course covering AI-era-proof Silicon Valley internships, 30 big-tech system designs, and hands-on open-source contributions. Using real-world cases from Netflix, Tesla, Meta, Tinder, and other big tech companies, you’ll design and scale 30 practical system designs. Finally, you’ll design your own service from architecture to database to scaling.

This is an online lecture that systematically organizes pathfinding and spatial partitioning algorithms used in game production.

This is a game development & algorithm course that focuses on the algorithms and principles of 2D game development from the ground up using Windows API and C++.

When learning Swift, the iOS programming language, it can be confusing when multiple concepts appear all at once. That's why I created this course with the principle that "when understanding a new concept, only previously learned concepts should be used." So this course is meticulously designed with a sequential structure between concepts, where only one new concept appears at each stage, and no other unfamiliar concepts appear at all. One concept per minute, 180 concepts total. From the basics of variables and constants to understanding memory structure from a CS perspective, and even the latest syntax for asynchronous processing. In 3 hours, you'll learn 180 core concepts in the designed order.

Through this course, you can acquire the concepts and practices of Information Strategic Planning.

This course provides a solid foundation in the essential linear algebra required for AI learning and research. It covers core concepts frequently encountered when preparing for AI graduate school admissions, reading research papers, and conducting research, as well as fundamental numerical linear algebra techniques.

This course explores microservice architecture and distributed environments not as a simple list of technologies, but from the “design perspective” required in real-world practice and technical interviews. Starting with the differences between monolithic architectures and MSA, it systematically covers gradual migration strategies, modular monoliths, clean architecture, and hexagonal architecture, clearly explaining why each choice is necessary and the trade-offs that come with it. Through hands-on exercises, you can directly verify the intentions behind each structure and learn about the core challenges inevitably encountered in distributed environments—such as data consistency, transactions, inter-service communication, and failure handling—through realistic scenarios. Based on actual questions and perspectives from Kakao interviewers, this course aims to do more than impart knowledge: it seeks to elevate your way of thinking about distributed systems to the next level.

The Code Puzzle Clear Challenge is a 4-week intensive training course based on "Learn to Code 1" in Swift Playgrounds, designed to develop "computational thinking" by giving commands to make a computer move as intended. By solving puzzle missions in each session, participants naturally learn to break down problems into smaller steps (decomposition), recognize patterns to organize repetitive rules using for-loops or functions, and make logical judgments to change actions based on specific situations. Beyond simply finding the right answer, participants reach a level where they can explain and refine "why they solved it this way."

Even if you know nothing about coding, you can create your own scheduling app in just 4 weeks. Simply tell the AI, "Make an app like this," and paste the code you receive into Swift Playgrounds. Over 12 sessions—3 times a week, 30 minutes a day—you will complete a real app featuring adding/deleting/editing schedules, categories and notifications, filters and search, and even a calendar view. Don't worry if you run into errors; just ask the AI, and it will fix them for you. Start the challenge now to learn how to collaborate with AI, rather than just studying coding!

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