Clean Coding: Learning Good Code Writing Techniques Through Cooking Analogies

Now is the era of development using AI. To create better, more accurate code and documents by better utilizing AI, methods are needed, so we propose suitable ones.

Explains the basic principles of large language models like ChatGPT, focusing on theory.

This lecture is designed for understanding even if you have no prior knowledge of what Secure Coding (Security Coding) is. After covering basic security coding concepts, it focuses on web service security. This was a special lecture presented under the auspices of OO University. It presents over 160 source codes with rich comments, pinpointing core topics and techniques immediately applicable in practice.

You can learn the concepts and methods of 'service design' needed when planning applications or web services built on LLM, a type of generative artificial intelligence (generative AI).

This enables junior developers to understand the entire development process from planning to code writing, deployment, and validation by using artificial intelligence as a development tool, allowing them to survive and thrive in the AI era by acquiring the full-spectrum capabilities needed.

This course is a systematic learning process for prompt engineering, which is a core technology for effectively utilizing large language models (LLMs) or generative artificial intelligence. It covers a wide range of topics from basic theory to practical techniques, as well as the latest application cases and security/ethical issues, providing practical help to LLM-based service developers, data scientists, and AI planners alike.

Problematization (문제화) is a term also translated as problem posing, problem framing, problem setting, or problem definition. This concept involves questioning known facts (like requests or common sense) from a new perspective, defining the problem, and devising methods to solve it. Problematization should be the starting point for all development, yet it remains insufficiently discussed within the field. Performing projects or developing programs is, in essence, planning to solve problems. This means they are related to problematization. To solve a problem, it must first be clearly defined. However, problems are mostly presented as vague requests. Therefore, the ability to transform vague requests into clear problems is essential to reduce unnecessary 'development waste,' facilitate smooth collaboration, and accurately grasp users' true needs. This lecture helps train 'the thinking of problem construction' through practical examples and tools.

What should be done when building a generative AI or LLM-based RAG (Retrieval-Augmented Generation) system, but the desired performance isn't achieved and there's no suitable solution? This lecture presents methods to improve RAG performance based on Cognitive Load theory. Through this lecture, you will understand the limitations of LLM context windows and learn how to effectively manage cognitive load in RAG systems. It is a practical-level theoretical lecture covering Chunk size and structure design, high-quality Chunk generation techniques, dynamic optimization, performance evaluation, and practical techniques.

"One name change, code transformed." "The key to readable code, 'naming for readability,' summarized from principles to examples." "Easy-to-read names begin collaboration."

You can quickly understand C language's basic concepts and grammar.

Starting from the origins of natural language processing technology, this provides a detailed explanation of the various language models developed in the journey leading up to the latest LLM models.

We explore methods for creating an AI judge by combining multiple agent frameworks such as CrewAI, LangChain, and AutoGen that enable the implementation of LLM-based multi-agent technology, along with knowledge graphs and reasoning systems.

We will examine methods for collecting and analyzing user requirements to plan LLM services.

We explore the limitations of LLMs, methods to overcome them, and the latest research topics.

Let's explore the types of applications or web services that can be built using LLMs.

Describes the need for LLM, its technical background, and basic concepts.

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

We provide CodeTree past questions, as well as algorithms and tips for solving them. We use C++, but since we don't use libraries, those who use other languages can also take the course. (Python code provided)

Coding Test [ALL IN ONE] ✔️ Complete with one lecture

Develop your ability to find the core of a problem and solve it with the 'Top 10 JavaScript Algorithms' that cover the most frequently asked types of problems!

Prepare perfectly for the Programmers Coding Essential Competency Certification (PCCE), from Python basics to competency certification!

A star instructor in IT development, artificial intelligence, and IT strategic planning provides an easy, detailed, and accurate explanation of the Python programming language.

This is a recorded video of the TDD online live meetup held in July 2025.

I hope that through this course you will gain a clearer understanding of grammar and gain confidence in solving problems.

I've vaguely heard the term refactoring, but I've organized it so that beginner developers who don't know how to refactor code using the IntelliJ IDEA editor can quickly learn.

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

We will refactor a web application built with Java + Spring Boot to Kotlin + Spring Boot and implement additional requirements. In the process, we will use Junit5, SQL, JPA, and Querydsl, and cover the pros and cons of various methods from the design and implementation perspectives.

Refactoring is one of the basic skills that a software engineer should have. This course is designed to explain and practice various code smells and refactoring techniques in a more practical way using IntelliJ and Java.

During our school days, the 'click' sound we heard in the computer lab... that was Minesweeper. In this course, we'll recreate those memories by implementing it with Python. Whether you're a beginner or even someone encountering Python for the first time, by following along line by line, you'll find that your very own Minesweeper game has been completed before you know it.

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.

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.