Prompt Engineering: Complete Guide

Practical Payment System Development Course, learn by code, and cover the knowledge needed to implement a real system.

We will learn about cases where companies such as Line, Google, Carrot, and Kakao actually improved MySQL performance. Let's go beyond simple performance optimization guides and understand the internal workings of MySQL and learn how to use it efficiently.

As AI rapidly permeates daily life and industries, attack techniques targeting these systems are evolving alongside them. This course is a practical, hands-on program designed to help you understand the latest security threats surrounding Generative AI and LLMs, automate security tasks using AI, and experience LLM jailbreak attacks and defenses firsthand.

This lecture covers RAG (Retrieval-Augmented Generation) system fundamentals and implementation using LangChain. Participants will understand RAG's core principles and learn to build and evaluate systems using LangChain.

How long are you going to manually look through 2,500 stocks every day? Searching through Naver Finance to find surging stocks after the market closes, Reading news to judge whether it's good or bad news, Checking foreign/institutional supply and demand one by one, Opening charts to analyze patterns... Aren't you repeating this every single day? I used to do that too. I spent 2 to 3 hours after work analyzing stocks, and yet I still missed more stocks than I found. With over 2,500 stocks across KOSPI and KOSDAQ combined, it's impossible for a human to see them all every day. --- So, I built a system. I created a system that automatically analyzes 2,500 stocks every day after the market closes. - Automatically collects market prices, supply/demand, and news - AI (Gemini) reads the news and determines if it's positive or negative - Scores stocks out of 15 points based on 6 factors - Selects only the stocks that pass the criteria and calculates entry, stop-loss, and take-profit prices - Sends notifications via Telegram Now, I just check my phone after work. Additionally, every Saturday, the system analyzes its own performance from the past week and automatically adjusts stop-loss lines, take-profit lines, and holding periods. It is a structure where the system learns and improves on its own. --- But I am not a developer. I didn't write the code for this system myself. I gave all the instructions to the AI verbally. "Filter out stocks that rose more than 5% today with a trading volume exceeding 50 billion won." "Send these 3 news articles to Gemini and have it judge if they are positive." "Create a scheduler so this runs automatically every day at 4 PM." When I speak like this, the AI (Claude) generates the code. This is "Vibe Coding." --- In this course, we will build this exact system. Over 58 lessons, we will build the system I actually use every day from start to finish. Starting from data collection, AI news analysis, scoring engine, signal generation, Flask API server, Next.js web dashboard, Telegram automatic notifications, and even the self-learning system. The final product is not a Jupyter Notebook. The final product is a web dashboard and Telegram notifications that actually run every day. You don't need to know how to code. In every lesson, I will show you how to talk to Claude, and if you follow along, you will get the same results. --- Recommended for: - Office worker investors who lack the time to analyze stocks every day - Those who want an automated system but don't know how to code - Those curious about quant/system trading but don't know where to start - Those curious about how to utilize AI in practice --- ⚠️ This course does not guarantee investment returns. This is a programming course on building your own stock analysis tools. Actual investment decisions are the responsibility of the student.

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

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.

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.

This video shows effective ways to link internal company data to sLM, and practical solutions for various issues from sLM adoption.

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.

“My idea can make money? Is AI monetization really possible?” Are you frustrated with the same paycheck every month? Do you have brilliant ideas in your head but feel lost on how to actually get started? Everyone says ‘AI’ is the trend, but does it sound like a distant story for someone who isn't tech-savvy? What if you could turn your ideas into ‘selling digital products’ and even create a system that generates income while you sleep—even if you don't know a single line of code or have any marketing experience? This course is a practical guide that teaches you exactly how to do that.

WordPress Post Scheduling, Thumbnail Auto-Registration Program Code - Get Yours!

Create a program using the GPT API, and even generate images and videos!

We introduce basic prompt patterns for coding and advanced API prompt patterns for leveraging artificial intelligence.

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

It's okay even if you don't know the first thing about coding. In this AI era, all you need is an idea and AI will write the code for you! This course is not simply about learning a programming language. It's a practical course where you learn 'the most modern development method' - giving commands (prompts) to the powerful AI code editor 'Cursor AI' to directly create the programs you've imagined.

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 the easiest way to handle AI with Spring AI. Let's learn Spring AI by building a RAG chatbot.

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

AI, the Key to Opening the World of Statistics "AI, by enabling easy mastery of complex statistical principles and analysis techniques, uncovers hidden meanings in data and provides insights for better decision-making. AI is now beyond a complex statistical calculator; it is a companion supporting statistical thinking."

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

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.