AI Agent Engineering

Claude Code handles judgment and execution, while n8n takes care of triggers, connections, and scheduling. By following the sequence of Concept → Connection → Practice, repetitive tasks are designed into a flow of Input → Judgment → Execution → Verification → Delivery. With error handling, retries, and human approval included, the system operates unmanned through scheduled execution. Even non-developers can build their own automation systems without having to learn coding from scratch.

We design and implement AI agent systems that go beyond simple chatbots to perform tasks autonomously. From Sense-Think-Act loop-based architectures to LangGraph cyclic structures, RAGAS and LangSmith-based quantitative evaluation, and operational guardrails, you will complete your enterprise-grade agent engineering capabilities through hands-on practice of the entire process.

AI writes on Slack and Notion for me? Work smarter with MCP, which goes beyond the limits of existing AI!

Even when using AI, the reason you’re still busy lies not in the tools, but in how the work is arranged. By asking four questions—roles, flow, handoffs, and exceptions—you can turn your work into a single blueprint, separate what can be handled by rules from what requires judgment, and reduce how often you need to call on AI in the first place. Use an Excel file containing 1,000 transactions to lock the standards into the tool and generate reports, break tasks down with sub-agents, and hand off what can’t be done to another AI, receiving only the results and carrying on. Finally, connect a messenger as the entry point and add four safety measures, completing the conductor’s role of calling on AI only where needed rather than handing everything over across eight installments, including the OT.

This is an 18-lesson course across 5 modules designed to transform Generative AI LLM agents—which often drain money through API costs—into a profitable structure by controlling expenses with model routing, cascading, caching, and loop guardrails. You will personally build everything from analyzing real-world cases of "cost bombs" to profit-and-loss simulations and architecture design projects. We recommend this course to AI developers and makers burdened by API costs, as well as those planning or operating agent-based services.

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

In the generative AI era, anyone can use it, but those who use it well are different. For those new to GPT, Gemini, and Claude, you will fully understand the world of AI through 100 practical prompts that you learn by actual input.

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.

Master the complete lifecycle of building modern Generative AI applications using Large Language Models, Retrieval-Augmented Generation, and Agentic AI systems. Learn to design enterprise-grade AI solutions from prompt engineering to deployment, combining LLMs with vector databases and external knowledge sources for production-ready applications.

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.

After ChatGPT was released in 2022, AI has become a very close software in our lives. The performance of models is improving day by day, and many new software applications that didn't exist before are emerging using AI. In 2025, as AI agents become a hot topic, many people are starting to develop AI agents. You may have heard the term AI agent, but this is an introductory tutorial that will help you understand what an AI agent is, why it has suddenly become a topic of discussion among so many people, how to create an AI agent, and how to easily build one using ADK.

It’s okay if you don’t know how to code. This course focuses on the experience of using AI to build an ad-revenue-generating Android app from scratch and successfully launching it in just one day. Many people stop at these stages: “I built the app, but how do I monetize it?” “I tried adding ads but got stuck on AdMob, policies, and reviews.” “I gave up right before launch because of the privacy policy.” In this course, we will navigate through every "drop-off point": 👉 Idea → App Creation → Ad Integration → Store Launch Essentials → Actual Deployment. We let the AI do the work, and we make the decisions. The goal is to complete an app with a "functioning revenue structure" within a single day.

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

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."

Adding Copilot to MS Office? The perfect guide to maximizing work productivity! We provide a systematic learning process for effectively utilizing M365 Copilot in practice.

$0 model fees, infinite visuals completed with NanoBanana All-in-one visual creating for diverse content designs

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

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

: "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 covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.