Learn how to ask ChatGPT for the results you want and verify the sources and outcomes of the materials. This is a 70-session course that begins with hands-on practice in documents, data, and writing, then progressively expands to the OpenAI API, RAG, agents, evaluation, and operations.

This is an introductory Java course designed so that even those starting programming for the first time can follow along. You will systematically learn everything from JDK 21 environment configuration to variables, data types, control flow statements, arrays, strings, and the core concepts of Object-Oriented Programming (OOP) such as classes, inheritance, polymorphism, and exception handling. Rather than simply listing syntax, we explain "why it works this way" to help you build a solid foundation.

"Developer Portfolio Completion Practice for IT Job Seekers" is a practical course designed to transform projects created in class from simple outputs into portfolios and interview materials that can persuade recruiters. It covers step-by-step how to organize projects, design the first page, expand case studies into structured formats, and connect these elements to interview answers, application routines, and operation/improvement records. This course is particularly suitable for graduates and entry-level developers who have created a portfolio but lack confidence in it or feel lost about what to do next. Through this course, learners will move beyond simply having "made something" and learn how to reconstruct their projects into "documents and evidence that can be utilized for employment."

While LLMs are currently transforming the development environment, what truly matters is not just "writing code on your behalf" but integrating them as features into a service. This course provides a step-by-step guide to implementing a lightweight yet polished Tarot reading service using Next.js and the OpenAI API. In the first stage, we will build an MVP that works without a backend, connecting the user input flow (questions/threads/card selection) to result generation. In subsequent stages, we will expand the functionality by building a backend, implementing general login and OAuth, adding community features, and creating a reading dashboard. Finally, we will conclude by deploying to AWS and integrating Google AdSense to complete a service ready for actual operation. Additionally, we will cover understanding pricing structures and cost optimization strategies to ensure that LLM API usage costs do not become a burden.

This is a 'practice-oriented course' where you will build and deploy infrastructure for a system tailored to the appropriate environment.

This is a 'practical, hands-on lecture' where you can understand the cloud through everyday examples that anyone can easily grasp and learn how to build infrastructure, just as it was conducted in our offline classes.