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

The actual sequence of how I organized insurance for all four family members in one day with Claude—after learning from a registered letter from the district office that my father’s mandatory car insurance had been lapsed for a month. I gathered information scattered across six sources and turned it into a Google Sheets ledger, calendar schedule, and one-page card for my parents, while also showing the line where humans handle passwords, identity verification, payments, and consent all the way through.

I used to spend hours writing blog posts myself. I wasn't good at writing; it would take me 30 minutes just to come up with a title and an hour to create a thumbnail. When I included the time spent thinking of social media posts, it sometimes took half a day just to complete a single article. Even though I was good at speaking, I struggled to organize those thoughts into writing. I enjoyed audio broadcasting, but the task of turning it into a blog felt like a chore, so I always put it off. However, everything changed once I started using Google Opal. Simply by uploading an audio file, the blog body, title, thumbnail, and social media posts are all automatically generated. What's more, by having it reference my own writing rules, it generates text that sounds like me and doesn't feel "AI-like." In this course, you will be able to build the exact workflow I use through the shortest possible route. No programming experience is required. You can build an AI app just by giving instructions in Japanese. It's okay even if you don't do audio broadcasting. You can complete an article just by speaking about blog ideas as they come to you. You no longer need to struggle for hours to write a piece. Just by speaking, your blog, thumbnail, and social media posts are completed. That future begins today.

Connect the diagnostic basis from the previous lecture to the organization’s improvement plan. Review Shadow AI’s data flows and control application requirements, and write a control design document and red-team report containing observed evidence, impacts, limitations, action owners, and retesting criteria.

Turn meeting minutes, reports, transaction statements, and even proposal decks into Skills that automate repetitive work. Build and connect them in Claude and ChatGPT without coding to create your own automated workflows.

Latest version as of October 2026. This is a 299-lesson course created by YouTube’s “AI Adjunct Professor Lee Jong-beom” (54,000 subscribers). It guides you step by step, starting with how to open a browser tab and progressing to creating an AI employee team with Claude Code. It includes approximately 290 practice worksheets and 1,000 credits.

From tokens and context to RAG, agents, and guardrails, we examine how AI services work from a security perspective. We compare the concepts with the provided backend code and organize the areas to inspect across input, retrieval, and tool calls into a single attack-surface map.

This is a real record of resubmitting a KakaoTalk Channel that was rejected because “the association between the business and the channel could not be confirmed/verified,” without revealing the representative’s real name—only by revising the single line of business information at the bottom of the site and the reason-for-resubmission sentence. It also shows the steps taken on the day of approval to set up chat, automated replies, the AI Consultation Manager, and the welcome message, and then verify them on a customer’s mobile phone.

Review the AI service’s settings, including keys, access scope, call limits, execution permissions, guardrails, and logging. Compare the controls before and after while keeping other conditions unchanged, and review output handling to create the Mission 4-2 settings checklist and diagnostic record.

Based on the LLM Wiki architecture proposed by Andrej Karpathy, we are freely releasing a practical pipeline and MIT open-source starter kit that automatically compiles five scattered Markdown notes (8,615 characters) into nine wiki documents (23,659 characters) and a knowledge graph with 44 bidirectional [[wikilinks]] in just 1 minute and 42 seconds.

We will teach you about AI, especially Generative AI like ChatGPT, by learning about it from various angles and showing you how to use AI tools that can be applied in practice. It consists of content such as marketing planning utilizing Generative AI, and an introduction to and utilization of Generative AI tools helpful for marketing content development (ChatGPT, image Generative AI).

Which AI tool should I learn first? Stop worrying now! - Rated 4.8 by 80 students ⭐️⭐️⭐️⭐️⭐️ - ChatGPT, Claude, Gemini, Genspark, NotebookLM, Gamma, Skywork, Manus, Antigravity, Claude Code, MiriCanvas, Opal, CapCut, and more - Learn the core features of over 15 tools very easily over 20 days. - Through weekly assignments, we provide a course you can "internalize" rather than just "passively listen to." - All-in-one coverage: Prompt Engineering > Image Generation > PPT & Video Creation > Vibe Coding - 4 hours of lecture videos + weekly study materials + assignment certification system

This is a course on creating blog images using DALL-E 3. This course provides practical knowledge and hands-on opportunities from the basics of image generation technology to advanced usage techniques and problem-solving strategies.

The ultimate profitable service: I create fortune-telling services that keep running even while I sleep. With a service built in just one week, I generated 2 million won in revenue during the first month without spending anything on advertising. My second service, built recently in just three days, generated 340,000 won in net revenue in a single day. This is not just a simple 'click-and-go' fortune-telling service. I am in charge of creating fortune-telling services for one of Korea’s leading associations of professional fortune-tellers, and I also develop and operate fortune-telling services made using IP purchased from Naver Webtoon. Starting from cases I have operated myself, this course walks you through the process of creating a high-quality fortune-telling service for your own brand by conversing with AI—even if you have no technical background. You will implement everything from characters and stories to fortune-telling results, payment and automated delivery, and an admin dashboard, then connect customer acquisition through automated Threads posts, Meta ads, and YouTube content. This is a 'real' fortune-telling course focused not just on the fun of creating, but on monetization.

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.

1. Python coding study to obtain the AI certification, AICE Associate 2. Step-by-step Python coding study from basics to applications 3. Lectures by Professor Joongheon Kim of Korea University, a scholar in the field of AI

[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.

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.

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."

Textbooks teach the modules separately, but the real world is different. An active SAP center director builds a hypothetical dumpling factory from start to finish and shows, through actual implementation project screens, how FI, CO, SD, MM, and PP really connect and work together.