Mẫu prompt (Vibe Coding) dành cho nhà phát triển

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

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

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.

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."

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 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 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.

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

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

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.

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 who want to increase team productivity.

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.

Have you ever regretted focusing only on notes instead of making eye contact, or failing to accurately record meeting details after an important client meeting? Don't worry anymore! In this lecture, we'll help you build your own CRM assistant using Vibe Coding to summarize key information with AI and neatly save meeting content. You'll learn how to drastically reduce cumbersome document creation time, maximize work productivity, and revolutionize customer management!

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

ChatGPT: How Far? Series, Stock auto-trading app & web inv. report creation!

Practical Essential Skills for AI Use, Prompt Engineering Learn key skills to boost work productivity and business competitiveness with accurate, proper prompts.

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.

In this course, you'll master prompt engineering techniques directly applicable in real-world scenarios using the OpenAI API. You'll learn how to simultaneously boost efficiency and productivity in your daily life and work. Specifically, we'll help you gain interview confidence by automating the creation of customized resumes and cover letters for desired companies, as well as mock interview preparation.

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

[How Smart People Think and Question] – Author's simplified lecture! Generative AI era, good questions over answers.

Apply the latest trends of Generative AI directly to your work! The bible of Prompt Engineering lectures, packed with essentials

A ChatGPT lecture planned with 2024's latest information. Based on large enterprise & finance field content, it covers hands-on 3.5/4.0 prompt practice and diverse generative AI tool use.

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.

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.

How have others used ChatGPT in their daily lives? We are releasing actual conversation logs!

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!

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