A Quick Overview of C Language

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.

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

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."

👨‍🍳 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.

This course contains only the essential content about C, the basic language of all languages. It is recommended for those who are learning C for the first time.

This is an open course provided by Hanbit Media's book 'Study C Language on Your Own'.

The fastest way to build the foundation of coding tests for joining IT companies! #Picture-based explanation #Code writing know-how #Companies you can go to #Only necessary questions

Secure Coding in C covers concepts such as buffer overflow, memory management, and vulnerability prevention to ensure the development of safe and reliable software applications.

"I want to become a game developer!" For all beginners who aim to become game developers, Jushin Game Academy has prepared a C++ lecture for pure beginners! This is a lecture that explains the grammar in an easy way so that even complete beginners can understand it easily, rather than going into depth. Students who want to study in depth, please wait for the advanced C++ lecture that will be opened later!

A must-take course for anyone thinking of becoming a Windows programmer! Have you studied C/C+, data structures, and operating system theory? If so, studying system programming is the answer now. Now it's time for practice!

This lecture covers how to properly implement a linked list-based linear data structure using C language. You can understand the structure of the DB as well as the linked list at once.

This is a lecture on 'Data Structure and Practice' by Professor Kwon Oh-Heum of Pukyung National University. You will learn about data structures through examples and practice using C.

If you can master DB and programming, you should be more than halfway prepared for the information processing engineer exam. Let's take a look at the DB and programming parts, which are worth 45 to 55 points in the practical exam, and pass the written exam steadily.