Complete Your Report with ChatGPT: A Hands-On AI Class for Building Logic, Planning, and Results

ChatGPT, which used to only answer questions, now works directly on my computer. I give it instructions in Korean without typing a single line of code and receive the results as files. This six-part series, including the orientation, explains Codex’s workflow of context, planning, execution, and deliverables, then covers everything from safely defining a working folder to organizing files, creating tables with sources, and setting up scheduled executions that run automatically at a specified time.

The “AI Team Members Do It All” online course is a hands-on program where you learn to use AI not simply as an automation tool, but as an “AI team member” that works alongside you in carrying out practical tasks. The course is structured around common real-world workflows, including market research, proposal writing, strategy report creation, brand content visualization, project promotion and operations, and post-project management. Participants assign various AI tools—such as ChatGPT, Perplexity, Copilot, Canva, Gamma, Miricanvas, and Vrew—to roles including planning partner, strategic research partner, design partner, and operations support partner, and use them to complete actual work deliverables. Across 30 sessions, you will learn step by step, from the fundamental mindset for working with AI to practical prompt writing, market research, proposal and report writing, brand content creation, and project operations. By following the course, you can develop the AI collaboration skills needed to work independently like an entire team.

We solve problems that are difficult to answer with practical research experience and proven prompts.

We solve the challenge of knowing Python syntax but struggling to build services through hands-on experience at Naver and step-by-step practice.

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

Customer analysis completed with Excel and Orange, from cross-selling to A/B testing and churn risk management all at once

Even if AI quickly generates an SQL draft, people must judge the table structure, relationships, performance, and data consistency. Using MySQL and DBeaver, you will gain hands-on experience with everything from tables, columns, data types, PKs, and FKs to DDL, database modeling, SQL fundamentals, indexes and EXPLAIN, and transactions, learning the standards for reading and validating AI-generated results.

It doesn’t stop at following along to create a sample game. Using ChatGPT- and Codex-based vibe coding, you’ll learn the entire process through a real launch project: from game planning → development → mobile builds → AdMob ad integration → publishing on ONE store, Google Play, and the App Store.

Mastering difficult AI with just one single analogy?! A first step into AI principles, understanding through core concepts rather than just terminology.

[Up-to-Date Knowledge for Current Times] 1. Changes brought by AX, ChatGPT, and robot technology. 2. Commonalities of Blockbuster-Kodak Film-Nokia. 3. Five Current AX Keywords. - OOOO coin to maintain dollar hegemony. - Musk's OOOO to cut government operating costs. - Trump's OOOO strategic reserve. - China's OO kindergarten, OO receiving private education. - China's OO factory, with no workers, OO is no longer needed. 4. ChatGPT/Gemini/Grok - Write prompts based on previously learned content and compare results - Generate images with Claymotion infographics

Are you explaining the same task to AI from scratch every time? A working developer is sharing all the settings they refined over seven months of using AI. Even non-developers can use AI to follow along and build a harness, then actually hand over one of their repetitive tasks to AI.

The real story of an AI-native company run by GolbinHacker, the 1st place winner of Kakao AI TOP 100 and author of the bestseller "The Best Prompt Engineering Lecture." It explores how just two developers build and operate a service, along with the new competencies developers and organizations need in the AI era through real-world cases.

You know about AI agent frameworks, but understanding how they work and applying them in practice can be difficult, right? Drawing on firsthand experience from Silicon Valley, we’ll guide you from the core principles to practical applications.

Learn what JEV is in simple terms first. Then follow the process of checking the results in the TypeSafe AI Playground and creating a Mac app that recommends emojis matching a sentence by making verbal requests to Claude Code. From signing up and connecting your API key to making your code public on GitHub, learn together through five videos and learning materials that include screen captures and prompts you can copy.

"The resumes and cover letters companies want! Providing all-in-one ChatGPT prompts for fast and effective writing🚀" Increase your chances of getting hired with powerful job-specific keywords and differentiated storytelling!

Learn how to create a team of AI Agents with Grokbot that goes beyond simply chatting with AI to perform development, research, design, and operations tasks on your behalf. Build everything hands-on—from Agent design to Prompts/Rules, browser, terminal, and tool usage, Multi-Agent collaboration, Memory, Skills, Routines, cost optimization, and failure recovery—and ultimately complete a 24/7 AI Company system that performs repetitive tasks without requiring constant human instructions.

How long will you keep struggling with repetitive daily research and document writing? I, too, was an ordinary office worker who worked overtime every day trying to find key insights amidst an overflow of information. However, after integrating Gemini 3 into my workflow, I experienced a significant increase in work speed. Boost your productivity by utilizing Gemini in your tasks.

There may be people who have never taken my lecture, but no one has taken it only once. After teaching in person for so long, I have finally had the opportunity to create this online course. Since the commercialization of AI, I have produced and researched countless pieces of AI content. Based on that knowledge and experience, I have built a logical philosophy of my own and organized it into concepts that are easy for anyone to understand. For those who have been generating AI images without considering the underlying concepts, I will instill a proper foundation in you. Once you take this course, you will be able to create any AI image in the future. Have you never created an AI image before? That’s perfectly fine. You don't need any prior experience in AI image generation. By simply learning and practicing through this lecture, you can become an expert in AI content creation.

This is a practical course that uses Codex to connect business planning, website creation, marketing materials, task organization, and email automation. Even if you are not a developer, you will learn how to delegate tasks to AI and refine the results using Notion, Linear, Figma, and Google Workspace in an actual workflow sequence.

Based on over 100 deep learning training sessions, this course systematically organizes the core foundational theories that students found most challenging. The course connects mathematical intuition, model learning principles, and code implementation step by step in a way that even non-majors can understand, deeply covering the fundamental structure and operating principles of how AI models learn, rather than just library usage. This is a practical introductory course designed to help you grow into a skilled engineer who understands AI principles by implementing core deep learning foundational technologies such as gradient descent, loss functions, optimization, perceptrons, multilayer neural networks, and backpropagation through both formulas and code.