Prompt Patterns for Developers

This lecture is designed to be easily understood even if you have no prior knowledge of Secure Coding. After covering fundamental secure coding concepts, it focuses on web service security. This course was originally conducted as a special lecture hosted by OO University. It provides over 160 source codes with extensive comments, pinpointing core topics and techniques that can be applied immediately in the field.

Explains the reasons why LLM is necessary, the technical background, and basic concepts for LLM planners and LLM application planning managers.

Without a single formula or line of code, this penetrates the essence of basic statistics necessary for AI development and application.

By enabling junior developers to use AI as a development tool to understand the entire development process—from planning and coding to deployment and verification—we empower them to survive and thrive in the AI era with the full-spectrum capabilities required.

This course is a systematic program for learning prompt engineering, a core technology for effectively utilizing Large Language Models (LLMs) and generative AI. It covers a wide range of topics, from basic theories to practical techniques, the latest application cases, and security and ethics issues, providing practical help to LLM-based service developers, data scientists, and AI planners alike.

Problematization is a term that can be translated as "raising a problem" or "problem framing." It can also be interpreted as problem setting or problem definition. It is a concept that involves questioning known facts—such as requirements or common sense—from a new perspective, defining the problem, and structuring the process to solve it. While problematization should be the starting point for all development, it is a topic that has not yet been sufficiently discussed in the field. Carrying out a project or developing a program is, in fact, the act of creating a plan to solve a problem. In other words, it is inherently linked to problematization. To solve a problem, the problem must first be clearly defined. However, most problems are given in the form of vague requests. Therefore, having the power to transform vague requests into clear problems can reduce unnecessary "development waste," facilitate smooth collaboration, and accurately identify the true needs of users. This course helps you train your "constructive thinking" regarding problems through practical cases 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.

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

"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.

👨‍🍳 Like cooking code, neatly and deliciously! 『Clean Coding』 is a code cooking class for chef-like developers, where they joyfully learn clean coding through a cooking analogy. 🍽️

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 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.

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.

We will explore the types of applications and web services that can be built using LLMs.

Explore the fundamental principles of large language models like ChatGPT.

To enable office workers to actively and effectively use AI in their work, we provide various techniques for reducing 'Hallucination' (i.e., nonsensical) answers and accurately eliciting desired responses.

It's structured to enable understanding of ChatGPT and text generation AI, learning effective real-world use, practice via diverse examples, and direct application.

Learn AI utilization methods and performance improvement strategies tailored to real-world business situations. (i.e., you won't learn things like automatic short-form video generation.) This is a practical course where you learn to leverage AI not merely as a tool, but as an ultimate instrument for business efficiency. By utilizing various generative AI and the latest AI agents such as ChatGPT, Gemini, NotebookLM, Gesnpark, Skywork, etc., you will master AI prompt utilization → AI data analysis → and AI task automation implementation, all at once. This class is optimized for planners, marketers, managers, founders, and others who wish to acquire business productivity and performance enhancement strategies directly applicable to their work.

A basic textbook and practical guide covering principles and practical uses of various generative AIs like ChatGPT and Claude, and for their effective introduction and utilization.

A quick, essential lecture for mastering ChatGPT! Let's learn fast!

The capabilities of AI can expand infinitely depending on how you write your prompts. The benefits gained from collaborating with AI depend on the clarity of your questions and whether you provide sufficient background information. Now, please make full use of GPTs to perform efficient and purpose-driven tasks.

I will tell you the "formula" for creating 챗GPT prompts. If you apply only this formula, good prompts will pour out.

Stop copy-pasting code! 🙅‍♂️ This is a "real" conceptual lecture that dives deep into everything from how agents work to their architecture and design philosophy. Beyond just learning how to build them, I will help you develop an eye for designing entire systems. Build a solid foundation here that remains unshakable amidst the technology trends of 2026! 🧠✨

This is a lecture directly from the author of <Prompt Engineering>. Learn to use ChatGPT, Bing, Bard, HyperCLOVA X, and more with ease.

Master prompt engineering perfectly, an essential skill for developers in the AI era.

Throw away those simple services you can make with vibe coding in just 10 minutes! You can learn 'real' practical vibe coding. Let's create advanced services at the level of actual services according to planning and design with Cursor AI NCOP. No Code, Only Prompt

This course goes beyond simple trends, covering how to systematically learn to collaborate with AI tools, verify and improve output quality, and build and deploy applications from start to finish. Anyone can take this course, from developers interested in AI to team leaders looking to boost team productivity.

AI literacy refers to the "ability for general users, not just technicians, to effectively utilize AI in their practical work and daily lives," as well as the "competency to critically evaluate AI." This is a practice-oriented literacy course designed for non-experts to understand the core knowledge for "utilizing" AI well—covering everything from prompt engineering to security understanding, expansion, automation, and the structure of language models.

This course is a systematic program for learning prompt engineering, a core technology for effectively utilizing Large Language Models (LLMs) and generative AI. It covers a wide range of topics, from basic theories to practical techniques, the latest application cases, and security and ethics issues, providing practical help to LLM-based service developers, data scientists, and AI planners alike.

Learn the core techniques of 'Prompt Engineering' to get exactly the answers you want from AI. From a complete beginner's first steps to expert practical applications, maximize your AI utilization skills!

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

The "How Far Can You Go with ChatGPT?" series: Creating a Stock Auto-Trading Application and Web Investment Reports!

This course is a question-focused training program that uses ChatGPT to directly design practical questions needed in the workplace and expand them into idea generation, report writing, and problem-solving. It is structured around hands-on practice, covering everything from creating good questions to team workshops, Why-based thinking, and question template automation, providing working professionals with question design and critical thinking skills they can immediately apply in the field.

This course introduces core principles and practical uses of various generative AI technologies (text, images, video, music), helping foster creative problem-solving skills.

This is a practical introductory course designed to help general office workers utilize generative AI as a business partner rather than just a simple tool. The objective is to develop the ability to use AI safely while complying with security and copyright standards, based on an accurate understanding of its operating principles and limitations. From the core principles of prompt engineering to streamlining text-based tasks such as planning, reporting, emailing, and minutes-taking, as well as Excel data analysis and the use of images and PDF documents, students will learn step-by-step. This helps drastically reduce time spent on repetitive tasks and secures the practical capability to handle multiple roles. Beyond individual use, the course covers how to build team-level work templates and standards. It is an action-oriented curriculum designed to ensure that participants possess work automation assets that can be applied immediately to their jobs after completion, leading to productivity improvements across the entire organization.