Vibe Coding with Google Antigravity — From Installation to Developing Data-Integrated Apps

This course is a 16-session, approximately 9-hour-and-30-minute practical course for developers with a foundation in Streamlit who want to build web apps ready for real-world deployment. Streamlit is a tool that can display a screen with just a few lines of code. That makes it easy to get started, but when you try to use it in practice, you run into a different set of challenges. How do you add login functionality? Where and how should passwords be stored? How can variables be shared across multiple pages? How do you prevent the entire screen from rerunning every time a form is submitted? This course addresses these challenges one by one. In the first half, you will review dataframes and chart visualizations, date and file-upload widgets, and Session State while building a mini dashboard. You will then begin the first project: an NLP analysis app. After setting up an Anaconda virtual environment and installing spaCy, neattext, wordcloud, and deep_translator, you will complete a single app by adding text statistics, part-of-speech analysis, word-cloud visualization, multilingual translation, and Korean sentiment analysis. You will also learn how to improve the app’s overall quality by structuring the interface with st . columns and st . expander and adding branding to the sidebar. The second half focuses on service-level features. You will manage member data with SQLite, examine the risks of storing passwords in plain text, and securely handle passwords using SHA-256 hashing. The course then covers theme customization, multi-page layouts and URL slugs, passing variables between pages, smart reading that can handle txt, PDF, and docx files, and controlling reloads with st . form and callbacks. The final three sessions cover advanced Python classes. By learning about their internal workings, encapsulation, inheritance, and special methods, you will build a foundation for structuring your code effectively. By the end of the course, you will be able to elevate Streamlit apps from something made “for practice” to something that is genuinely “usable.”

This course is a practical program on using Claude not merely as a chatbot that answers questions, but as a collaborative partner that works alongside you on real tasks. It consists of 2 parts and 18 lessons in total. First, we cover the basic principles of how generative AI understands and generates language—including semantic analysis, ambiguity, and statistical language models—to lay the foundation for using Claude effectively. With this understanding, you will be able to design more sophisticated prompts. Next, we automate the tasks you encounter every day in your work, one by one. From automatically organizing emails, extracting action items from meeting minutes, and cleaning up Excel data to writing reports and proposals, extracting information from invoices and receipts, and automating daily briefings, the course covers a broad range of document and data-related tasks. In the latter part, we take things a step further. Through hands-on practice, you will learn to automatically generate PPT slides, integrate external services, create schedule-based automated routines, use Skills plugins, conduct parallel competitor analyses, write SOPs and internal policies, automate the Chrome browser, and even build real apps through vibe coding. Beyond simple question-and-answer interactions, you will develop practical expertise in working with Claude—from requirements analysis and documentation to automation and development.

When you look back on a day at work, certain tasks repeat themselves. You search for information, write reports, attend meetings and take notes, create Excel spreadsheets and PowerPoint presentations, and organize and share the results in documents. These five tasks are essentially the backbone of office work. This course covers those five stages in order, assigning one suitable AI tool to each. Perplexity is used for research and organizing information, Claude for writing documents and creating drafts, Naver ClovaNote for automating meeting minutes, Microsoft Copilot for support with office tasks, and Google Gemini for integration with Google services. This is not a course that simply lists tools; it teaches you how to decide which tool to insert at which point in your workflow. Each tool is covered in the same three-step format. In Lesson 1, you will learn the background behind the tool, what it does well and poorly, and where the boundary lies between its free and paid plans, before taking a look around the official website. In Lesson 2, you will learn the basics by going through the menus and settings. In Lesson 3, you will practice using real-world work scenarios. Examples include creating business and business-trip report templates, researching popular restaurants in Jongno, Seoul and organizing the information into promotional presentation materials, drafting a business report PPT introducing a product to a client, recording a sales report meeting and turning it into meeting minutes, creating a marketing logo image, and preparing approval forms and accounting ledgers in Google Docs. In particular, this course spends considerable time showing how much the results can vary depending on how you phrase your questions. You will see firsthand that even the same request can produce completely different results when written in two lines versus ten, using specific instructions such as generating tables, creating charts, specifying list formats, and downloading files. All you need is a PC connected to the internet and a web browser. You will need to sign up for each of the five services, and the course is based on their free usage options. However, each tool has different limitations. Microsoft Copilot becomes especially useful when integrated with Office applications, so its value increases significantly in an environment that uses Microsoft Office. For real-time recording practice with ClovaNote, the mobile app is more reliable than a PC microphone. These details will be explained as they come up in the relevant sections. It is perfectly fine if you have never used an AI tool before. By the end of the course, you will be able to decide, "Which tool should I open for this task?" and formulate questions on your own to get the results you want.

This course is a 26-session, approximately 13-hour hands-on course for those opening Figma for the first time, covering everything from the fundamentals of UI design to the latest AI automation features. Figma has now become an essential tool for UI design, but with so many features, it can be overwhelming to know where to start. In particular, if you do not properly understand concepts like Auto Layout and Components, you will keep taking workarounds and ultimately remain stuck manually moving shapes one by one. This course builds up these concepts step by step through examples. The first part covers the interface, vector tools, and graphic styles. Once you learn how to work with shapes and paths and register color and text styles as a system, your workflow speed will change. You will then learn the principles of automatically arranging elements with Auto Layout. The middle section focuses on Components and Variants. You will practice creating a single button, managing its different states, and building a structure that can be reused across multiple screens. In the responsive layout sessions, you will learn to design UIs that do not break when the screen size changes and extend them to mobile layouts. The final six sessions are what set this course apart. You will learn how to import existing web pages into Figma using the 'html . to . design' plugin, turn designs into actual web pages with Figma Site, and generate code by entering prompts with Figma Make. The latest Figma AI features are also covered. You can follow along even if you did not major in design or have never used graphic tools before. By the end of the course, you will be able to design web and mobile UIs yourself and reduce your working time with AI features.

This course is a 37-lesson, approximately 14-hour program that covers OpenAI’s AI coding agent, Codex, from start to finish. AI coding tools are now commonplace. However, most users remain at the level of accepting autocomplete suggestions or asking questions in a chat window. Agentic tools like Codex can do much more than that. They can read an entire project, modify multiple files simultaneously, run tests, and find and fix errors on their own. The problem is that they require an equivalent level of control. If you do not know what to allow and what to block, or how to teach the tool your project’s rules, you will end up cleaning up the code it creates afterward. This course focuses on how to establish that control. In the beginner section, you will learn installation and your first conversations, file editing and session management, and slash commands, while building a foundation in prompt writing. Through hands-on practice, you will internalize three principles: making clear requests, breaking down tasks, and verifying the results. The intermediate section is where the main content begins. You will configure behavior with config.toml, teach project rules with AGENTS.md, and manage memories with Memories. You will design safety boundaries yourself by combining the sandbox with four types of approval policies. The course then covers thread separation and parallel work, planning mode, connecting MCP servers, and creating custom skills based on SKILL.md. Finally, after covering web searches and Git automation, VS Code and Cursor integration, and hands-on FastAPI practice, you will examine Codex’s internal protocol, the SQ/EQ queue model. Understanding how the tool works changes how you respond when problems arise. The entire course follows the process of building a single service called TaskFlow. Rather than learning each feature in isolation, you will experience, in sequence, when and why each one is needed in a real project.