Computational Thinking (Part 1)

In this lecture, you can learn linear data structures and algorithms.

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

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.

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.

It improves logical thinking skills, develops an understanding of how to use programming tools, and develops the ability to design algorithms for problem solving.

This course approaches microservice architecture and distributed environments not as a simple list of technologies, but from a 'design perspective' required in actual work and interviews. Starting from the differences between monolithic and MSA, it progressively covers incremental transition strategies, modular monoliths, clean architecture, and hexagonal architecture, clearly explaining why each choice is necessary and the trade-offs involved. Through hands-on practice, you can directly verify the intent of the structure and learn about core issues 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 not just at knowledge acquisition, but at elevating your way of thinking about distributed systems to the next level.

✅ Out of the entire series (1) ~ (7), (4) data structure, algorithm, object-oriented, programming language ✅ CS101 series lectures - From basic computer theory to the latest practical examples - Provides a wide range of basic knowledge

Learn Python from scratch by fully utilizing ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly experiencing coding and developing problem-solving skills through example problems and practical exercises. After mastering Python's basic syntax, you can build your skills by solving various problems in Level 1 and Level 2. Furthermore, you can identify and supplement your weaknesses through an Exam structured like a real test. By regularly solving problems and utilizing ChatGPT, students can have a memorable learning experience without feeling bored.

Problematization is a term that can also be translated as problem-raising or problem-framing. It can also be translated as problem-setting or problem-definition. It is a concept that encompasses the process of questioning known facts such as requests or common sense from new perspectives, defining problems, and working out ways to solve these problems. While problematization should be the starting point of all development, it remains an insufficiently discussed topic in the development field. Carrying out projects or developing programs is, in fact, about creating plans to solve problems. In other words, it is related to problematization. To solve a problem, the problem must first be clearly defined. However, problems are usually given in the form of vague requests. Therefore, having the ability to transform vague requests into clear problems reduces unnecessary 'development waste,' facilitates smooth collaboration, and enables proper understanding of users' real needs. This course helps train 'problem-constructing thinking' through practical cases and tools.

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

Computational thinking isn't something that only computer science majors learn. Every profession has problems that need to be solved, and computational thinking can be used to solve those problems.

Learn Java-based data structures and algorithms, and grow into a competitive coding expert with practical problems!

# Silicon Valley Internship That Won't Get Cut Even in the AI Era & Complete Course on 30 Big Tech System Designs & Open Source Practical Contributions All students who submit course missions can apply for an AI startup internship in Palo Alto, USA, with exemption from document screening and guaranteed interview opportunities. This course involves designing and scaling 30 real-world system designs based on big tech cases including Netflix, Tesla, Meta, and Tinder. Finally, you'll design your own service from architecture → DB → scaling, contribute to an actively operating open source AI coding agent project (achieving 1.8k downloads per week) to complete your portfolio, and finalize your resume.

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++.

2025 Unreal Certified Instructor – C++ Sparta Class is a free course designed so that even complete beginners with no programming knowledge can easily get started. Rather than complex theory or difficult mathematics, it guides you to naturally learn C++'s core concepts through the experience of directly writing and executing code. By the end of the course, you'll gain the confidence to write simple programs on your own.

Strengthen your coding skills through coding test problems by learning Python-based data structures and algorithms!

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.

Want to take your code to the next level? 🚀 For beginner developers, I've prepared the 'Python Design Patterns' 📖 course. Complex design know-how is made easy to understand with practical examples. In this course, you'll learn these things: 💼 **Practical Example-centric**: Real-world examples you can apply immediately 📚 **Mastering Classic Patterns**: Master GoF's core patterns 🐍 **Pythonic Tips**: How to write more concise and efficient code It will boost your confidence in code design! ✨

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.

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