(For Planners) LLM Application Service Case Analysis

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.

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.

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

Describes in detail the various language models developed from the inception of Natural Language Processing technology to the process leading up to the latest LLM models.

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.

You can learn the concepts and methods of 'service design' necessary when planning applications or web services based on LLMs, 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.

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.

👨‍🍳 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. 🍽️

We create an AI judge by combining CrewAI, facilitating LLM-based multi-agent technology, with knowledge graphs and inference 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.

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

This special lecture concurrently prepares for Microsoft AI-900 certification, featuring the latest content reflecting May 2025 exam scope, combining theory and practice, including AI overview, machine learning basics, computer vision, natural language processing, document intelligence, knowledge mining, and generative AI.

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

Through AI company reviews, we examine how AI technology will change our present and future through various cases. By examining the necessary elements for carrying out AI projects, we prepare for the upcoming AI Transformation.

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

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

[Introduction to Service Planning] Current planners from large corporations N and K will become online mentors and explain planning methods in detail to those who are taking their first steps as planners and those seeking a job in service planning.

We create an AI judge by combining CrewAI, facilitating LLM-based multi-agent technology, with knowledge graphs and inference systems.

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

"LoRA-based lightweight fine-tuning: Your first step to creating a customized LLM!" This course is an introductory hands-on lecture designed so that even those encountering LLMs for the first time can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading models → applying data → training → comparing results. In a short time, you'll directly experience the flow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, gaining an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

This is a practical guidebook for game business PM job seekers. Starting with the scope of work that business PMs do, we will teach you practical concepts such as BM analysis and improvement proposals, event planning, operation tool planning, indicator design and analysis, and how to write a portfolio.

This is a practical lecture on operational tools & back office and data analysis planning, which are tasks handled by game planning, service planning, and business PM positions.

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

Now, with the power of AI, anyone can easily plan apps and design UIs! It's okay even if you don't know coding or have no UI experience. AI tools like Claude and ChatGPT will turn your ideas into reality. With just a few questions, you can analyze target customers, design app structures, and even automatically generate UI screens. In this lecture, we will teach you step-by-step from the basics so that even those who are new to Figma can follow along. Even without drawing by hand, you can import existing website UIs at once with the HTML to Design plugin, and with AI tools like Google Stitch or readdy.ai, you can create high-quality screens in a few seconds. This lecture is perfect for anyone dreaming of starting a business, wanting to switch careers to a planner, or wishing to communicate with developers. Instead of complex theories, we will only teach practical know-how that you can immediately use. Now, with just an idea, anyone can plan app services!

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is the technology that has come closest to AGI at this point in time. In this lecture, we explore LLM and Agent technologies from a general public perspective.

In this lecture, we will look at service planning and design methodologies for planning services in the IT/tech field, as well as various soft skills that service planners must have. Finally, we will analyze the service using the example of an AI voice recognition service, a UX service introductory lecture for beginners.

This course provides UX principles and practical know-how necessary for planning and designing AI products. We will explore user-value-centered AI utilization methods, UX planning and design methods using AI, core UX principles and theories learned through everyday design cases, and UX research and data analysis methods for providing a better experience.

Based on an accurate understanding of black consumers, appropriate countermeasures and strategies are acquired, enabling effective response to black consumers. Furthermore, it is designed to enhance the professionalism of service staff and improve job satisfaction.

If you're wondering what UX Writing is and why it's important, you'll find out by looking at examples of successful apps.

Have you ever felt frustrated when you were creating a B2B product and there was no content covering it? I will explain the similarities and differences between B2B and B2C products in an easy-to-understand way based on your actual career.

In the AX era where AI technology and UX design converge, what strategies should product teams use to design customer experiences? A 17-year veteran senior researcher from a major corporation and knowledge sharer with a PhD in HCI will share insights based on the latest trends, use cases, and research findings.