AI Agent Engineering

Learn context engineering techniques for creating high-quality AI agents through hands-on practice.

Innovation in Work Efficiency and Creativity – Agentic AI AI is now evolving beyond simple automation into a new stage where it can judge and execute on its own. Agentic AI is at the center of this change, serving as a core technology that helps businesses and organizations operate smarter. In this course, we have organized the content clearly and simply so you can understand how Agentic AI connects decision-making with execution and how it can be applied to practical work. Discover the essential knowledge for every professional preparing for the future right now.

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

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

This is an advanced course focused on designing and implementing Multi-LLM architectures and orchestration-centered Agent systems (Main/Sub, Tool, Task Runtime, Agent Registry) by strategically combining GPT, Gemini, and LLaMA (local) based on Spring AI and Spring Boot. Moving beyond simple LLM calls, the curriculum covers the implementation of scalable, stable, and continuously improving AI systems. This involves applying Agentic Workflow Patterns (Chain, Parallel, Routing, Orchestrator–Workers, Evaluator–Optimizer) and Multi-Agent structures, separating execution layers like RAG and external APIs/DBs via Tool/ToolRegistry, and utilizing DAG engines, YAML declarative workflows, and Validated DSL (validation immediately after loading). Furthermore, the course includes Circuit Breakers, Reactive Streams, Redis monitoring, parallel processing, and iterative evaluation loops. It expands from Thymeleaf (SSR) exercises to decoupled Front-end/Back-end architectures using React and REST, while integrating tool and agent runtimes via MCP (Model Context Protocol) to build AI architecture design capabilities at a production-ready level. The ultimate goal is to evolve beyond being a simple AI user who merely integrates APIs and writes prompts, becoming a developer capable of designing AI systems—explaining and balancing Multi-LLM, agents, workflows, declarations, and validation within a single execution architecture.

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.

"Why does my automated trading collapse in a bear market?" I have also deeply pondered this same question. Most automated trading logics on the market seem to generate profits during a bull market, but they lose their ability to respond the moment the market sentiment changes. To solve this problem, I have combined the know-how I researched myself over the past two years with the latest AI technology. In this course, you will learn how to directly design a 'Transformer-based deep learning model' that simultaneously reads macroeconomic trends and individual stock flows, and how to automatically train and deploy it in a free GPU environment. In particular, we will introduce sophisticated data normalization techniques at the hedge fund level to build an 'Intelligent Comprehensive Scoring System' that goes beyond simple indicators to incorporate news sentiment. To this, we add an 'AI Safety Gate' that implants the insight of a trader with 20 years of experience on Wall Street, adding a final layer of confidence from a human trader's perspective right before a purchase. Beyond simple buying and selling functions, you will directly implement the entire process of an institutional-grade algorithmic system by adding dynamic take-profit and stop-loss logic, eight self-recovery mechanisms, and real-time Slack reports.

<This course is part of the 'Wrtn AI Literacy Voucher Program', a collaboration between Inflearn and Wrtn, and is available completely free for elementary, middle, and high school students who are in the AI vulnerable demographic.> From the fundamentals of artificial intelligence to generative AI that creates text, images, and videos! Artificial intelligence is already being used everywhere in our daily lives. This course is designed to help you easily understand what AI is, how it learns, and how it works. Without complicated formulas, just follow along like listening to a story and you'll naturally become friends with artificial intelligence!

AI Workflow Automation + Passive Income Generation in Just One Click!!! The ultimate tool for workflow automation, Make—were you hesitant to start because of its complex settings and features? Implement the automation of your dreams yourself with step-by-step lessons that even beginners can easily follow.

This is our 'actual real-world workflow,' and we are releasing the 'onboarding video' used for planners and developers joining our company. It teaches you how to design service screens without a designer and create UX flows and prototypes even if you don't know Figma. Our company maximizes productivity by prototyping quickly during service planning to enable fast decision-making, finalize necessary features, and utilize them directly in front-end development. If the response is positive, I will upload more lectures on other "real-world workflows."

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.

If you want to create your own AI service without coding, this course is the perfect solution. Using the Dify no-code platform, you can create high-quality AI apps with just your ideas. Instead of complex theory, it's structured around hands-on projects, allowing both AI beginners and working professionals to develop practical skills.

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

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.

This is a Silicon Valley internship and 30 Big Tech system design & open-source contribution mastery course that ensures job security even in the AI era. In this course, you will design and scale 30 real-world system designs using cases from Big Tech companies such as Netflix, Tesla, Meta, and Tinder. Finally, you will design your own service from architecture to DB and scaling.

You can implement hands-on practice of infinitely generating cryptocurrency trading signals automatically using ChatGPT and Python, and backtesting and validating them. Additionally, you can learn how to combine all the strategies automatically generated by AI into a single strategy and apply it to actual trading.

"Mastering Model Context Protocol (MCP)" is a practice-oriented engineering course designed to help developers build secure, production-ready AI backends. Based on my experience helping thousands of students resolve confusion in LLM integration, Tool Calling, and backend architecture, I aimed to address the most common challenges through this course. "How can I build a reliable backend that an LLM can call securely?" "Should I choose SSE, stdio, or streamable-http?" "How can I scale MCP to a real-world application level using FastAPI, Auth0, and LangGraph?" "How should I structure MCP Tools, Resources, Prompts, and Context?" This course provides detailed, step-by-step guidance, from running a minimal MCP server to deploying a fully secured, Docker-based system. All lessons are practice-focused, centering on reducing complexity and providing clear, repeatable workflows for building modern AI systems. If you are tired of vague tutorials and want a clear, concrete, engineering-level understanding of MCP, this course was made for you.

You can learn the core concepts of complex Next.js in a short time. We'll teach you only the essential practical knowledge for those learning Next.js for the first time. Captain Pangyo's new Next.js course, who has been conducting framework courses for 8 years. You can learn the coding and learning methods of "Frontend Developers in the AI Era"! 😊

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

We're building an AI-powered video conferencing application with real-time AI agents, meeting summary features, and post-call functionality.