(For Planners) LLM Application Service Case Analysis

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

By enabling junior developers to understand the entire development process from planning to code writing, deployment, and verification using artificial intelligence as a development tool, it helps them survive and thrive by acquiring the full-spectrum capabilities needed in the AI era.

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.

This course systematically teaches prompt engineering, a core technology for effectively utilizing Large Language Models (LLMs) and generative artificial intelligence. It comprehensively covers everything from foundational 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 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.

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 concepts and methods of 'service design' needed when planning applications or web services built 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. 🍽️

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.

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.

Explains why LLMs are needed, their technical background, and basic concepts.

This explains the foundational principles of large language models like ChatGPT with a focus on theory.

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.

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).

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.

This is an applied web planning course that will teach you how the basic web planning course is applied to mid-to-large-scale projects and applied to practice. Students can master the skills and practices of each stage of web planning in the big data field. <<This VOD is a recording of an actual class and includes some sounds such as small talk, so please keep this in mind when purchasing~!>>

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.

This explains the foundational principles of large language models like ChatGPT with a focus on theory.

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.

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.

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.

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.

If you know that UT (usability testing) and user interviews are good, but don't know how to do them, gain confidence with this course!

This is a lecture covering LLM theory and practical examples based on <Large Language Models, Just the Essentials!> (Insight, 2025).

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.

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.

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

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!

In the age of information overload, 'communicating easily' is now the real competitive advantage over 'knowing a lot.' This course goes beyond simply polishing your writing—it develops your 'communication design ability' to identify the core message in a flood of information and deliver it at the right level for your audience. It consists of a compact curriculum of 7 lessons totaling 56 minutes. Say goodbye to boring lectures filled with theory! Through training centered on real-world examples (Before/After), you'll transform into an 'information delivery expert' who communicates best within your organization.

"Your first step to creating a customized LLM with LoRA-based lightweight fine-tuning!" This is an introductory hands-on course designed so that even those new to LLMs can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading the model → applying data → training → comparing results. In a short time, you'll directly experience the workflow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, and gain 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.