JEV Basics: Build My Own App with TypeSafe AI and Claude Code (Codex)

Can you create a service with your ideas even if you don't know how to code? With AI, it is possible! In this course, you will experience the entire process of turning an idea into a real web service using "Vibe Coding" tools used in the industry, such as Gemini, Lovable, Antigravity, Cursor, and Claude Code. You won't just learn how to use the tools; you will master a new way of service development in the AI era—from planning and deploying to integrating payments. Point 1. Master 5 Core Vibe Coding Tools - Hands-on practice with core features and applications of Gemini, Lovable, Antigravity, Cursor, and Claude Code - Understanding the Vibe Coding development method of collaborating with AI Point 2. Building a Real Service Without Coding - Hands-on process of planning and implementing a book recommendation web service - Understanding the entire service creation flow: Idea → Development → Deployment Point 3. Practical Skills for Service Launch and Operation - Understanding domain purchase, server setup, and the deployment process - Learning core operational technologies such as payment module integration and SEO settings

This is an introductory course for those using Claude Code for the first time. You won’t do the coding yourself—Claude writes both the code and the configuration files. Starting with creating a psychological test in the browser, you’ll build a household budget using card transaction records, create an escape room game, and make a travel itinerary that connects to external services like Google Calendar and Notion. Since you learn each feature as it becomes necessary, you’ll also understand why that feature is needed.

Even those who know nothing about coding will be able to create their own automated stock trading program by giving commands to AI in Korean!

The online course “AI Teammates Do It All” is a hands-on program that teaches you how to use AI not merely as an automation tool, but as an “AI teammate” that works alongside you on 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 follow-up management. Participants assign various AI tools—including ChatGPT, Perplexity, Copilot, Canva, Gamma, MiriCanvas, and Vrew—as planning partners, strategic research partners, design partners, and operations support partners, and complete actual work deliverables with them. Across 30 sessions, you will learn step by step, from the basic 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 to work on your own like an entire team.

I will teach you Vibe Coding systematically from the ground up, following the exact curriculum refined while teaching over 10,000 students by a former Tech Lead with 10 years of experience in New York and LA startups. Together, we will build my own service, 'Kagong Map,' from scratch, learning the entire real-world workflow—from research, development, and deployment to operation and automation by delegating tasks to AI agents. I promise you two things: first, you will grasp the big picture of how a service operates so you can judge the AI's output yourself; second, you will learn how to embed workflows and standards into the environment so the AI produces consistent results every time. When you make the judgments and the AI follows orders effectively, your ideas become real services.

Stop getting student-record planning. I’ll reveal the entire consulting playbook used by a college admissions consultant with 30 years of experience.

Your AI is no longer in the cloud. It runs directly on your laptop. Learn how to build a completely local Private AI environment using LM Studio and Ollama—for everything from data processing and document analysis to code generation. With no security concerns, no costs, and greater speed— move from simply “using” AI to “putting it to work” yourself.

Copilot used by working developers in the industry! From Copilot tips to unit testing and API integration testing, do it all with Vibe Coding! Leap forward as a 10x faster director with real-world industry know-how.

A practical introductory course on Claude Code for Unity developers! From installing Claude Code to Unity MCP integration, managing project conventions using CLAUDE.md, custom slash commands, and collaboration workflows—we will teach you everything you need to know for real-world application. Finally, you will gain hands-on experience effectively applying Claude Code to a Unity project by building a Survivor-style game from scratch.

Experience firsthand how conversations that once disappeared can become reusable assets again. With Hermes and Wiki, build a work system where decisions and their rationale are preserved!

When you use a chat-optimized LLM for classification, routing, and guardrails, it returns a string that you then have to parse again. This comes with hallucinations, type drift, delays of several seconds, and output-token costs. This course follows the architecture of Jev, TypeSafe’s first System One model: provide a state, and it returns typed decisions within a schema along with calibrated probabilities. The model does not generate strings. It covers, through concepts and code, why parallel sampling and RLCD (Reinforcement Learning for Calibrated Decisions) make those decisions fast, how to combine Choice · Score · Noul in a single request, and a hybrid approach that leaves structurally defined judgments to Jev and open-ended descriptions to an LLM.

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

It is difficult to complete a classification service using only AI API calls. Based on practical experience, I guide you through everything from implementation to deployment.

[Core Concepts of AI Coding Tools] Free Introductory Course

: "From Mathematical Foundations to the Latest Models, Completing the Deep Learning Pipeline with PyTorch (44 Lectures in Total)" The era of simply learning how to call model.fit() is over. From the very basics of artificial neural networks—differentiation and gradient descent—to essential PyTorch techniques used in the industry, and CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and step into the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.

This course teaches non-developers how to properly build, operate, and monetize a service using Claude Code. It provides template repositories and operational know-how so that non-developers and beginner developers alike can use Claude Code at the level of the top 1% of developers. This course will be especially helpful for those who want to build a service with Claude Code at a truly “professional developer” level; those who want to create a service capable of generating revenue through a one-person business or side project; those who have built something powered by an AI agent like Claude Code but are stuck because they lack the know-how to operate it properly; and those who feel overwhelmed as their solo project grows because bugs keep occurring and things become difficult to control whenever they add new features. The course also covers how to build a foundation for monetization and provides guidance on operating the service under the assumption that real customers will be using it. Once you have actual customers, processes such as monitoring errors occurring on the production server, server status, and logs are essential. However, there are surprisingly few places that teach these processes. In my course, along with this kind of detailed and professional operational know-how, I also explain how to enable AI to observe these monitoring metrics and data and take appropriate action.

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."

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

For those of you who have completed intermediate SwiftUI, it is now time to integrate AI into your apps. Complete an on-device AI app that runs locally without an internet connection using Apple Intelligence and the FoundationModels framework.

I will show you "where to start" through a case study of building a service with non-developers in just one day, and explain "how to manage and collaborate" using the example of designing the GitHub structure for the Selfish Membership team.