[Java Practical Project UI Edition] Building a Movie Information Application Based on Spring Core + JavaFX
In [Java Practical Project: UI Edition], we will create a movie information application that operates solely on pure Java technology using JavaFX. This course is designed to help you deeply understand the "structure connecting screens and logic" by directly implementing UI event handling, asynchronous logic, and user interaction flows in Java before moving on to web and smartphone apps. You will train your structural thinking by separating business logic and UI through integration with Spring Core, and learn how to solve UI performance degradation issues that may occur when fetching movie information from external APIs using asynchronous processing. Through this, you will clearly understand the principles of data flow, event listeners, and thread-based asynchronous processing, elevating your understanding of the Java language itself to the next level. In short, this course is a "practical stage to experience the essence of UI and the core of asynchronous processing with Java before moving to the web." Do not forget that this is not a class for just typing along with code, but a learning experience where you can personally master the principles of connecting UI and logic.
9 learners are taking this course
Level Basic
Course period Unlimited
๐ข Announcement: OpenClaw.AI Basics Part 2.5 Lecture Now Open
๐ข OpenClaw.AI Basic Part 2.5 Course Opening Announcement
Hello, I'm Kevin, the instructor for the OpenClaw.AI Master Class basic course.
I am finally posting an announcement as [Basic Part 2.5] Fundamentals of Multi-Agent Team Design and Role Separation has been released on Inflearn. :)
This Part 2.5 further expands the "AI Assistant in my PC" created in Parts 1 and 2,
This is a lecture focused on growing a single Telegram bot into a small AI team with divided roles.
๐[Go to OpenClaw.AI Basics Part 2.5 Lecture]
What we will build together in Part 2.5
- Using Telegram Forum Groups + Topic-based Routing
We will configure a multi-agent environment that operates two agents, content-planner and content-editor, with a single bot.
- To the /workspace/content/planning / /workspace/content/drafts folders
We will actually create a content workflow where planning deliverables and draft/edited versions are separated.
- Through the scenario of "generating ideas and outlines in the planner room โ refining the writing in the editor room," we will complete a realistic multi-agent collaboration routine based on manual copy-pasting.
Especially recommended for these people
- Those who have followed OpenClaw Parts 1 and 2 but are still making a single agent do everything
- Those who want to develop a Telegram bot not just as a "single chatbot," but as an AI team divided into a Planner and a Writer/Editor
- Solo creators, newsletter/blog operators, and YouTubers who want to organize their workflow by delegating content planning, drafting, and refining tasks to role-specific agents.
- Developers, planners, and PMs who are interested in multi-agents but want to start light in their current OpenClaw + Telegram environment instead of using a massive framework
Part 2.5 Core Curriculum at a Glance
- Section 1: For both existing and new students
Part 2.5 Joining Route A (5-minute environment check) / B (Minimum setup onboarding) Guide + Super simple review of OpenClaw UI
- Section 2: Single-agent vs. Multi-agent concepts,
Understanding the structure of how multiple agents are deployed within openclaw.json, and checking the current configuration with openclaw agents list
- Section 3:
- Define content-planner / content-editor agents
- Separate workspaces for /content/planning and /content/drafts
- Telegram forum group & planner-planning / editor-editing topic creation
- Find Group ID / Topic ID โ Complete agent routing by topic
- Section 4:
- planner โ editor semi-manual collaboration practice (based on human copy-paste)
- Preview of the 4-agent automated collaboration pipeline (Leader/Planner/Editor/QA) to be covered in Part 3
Checklist before taking the course
- It is best if you have the WSL2 + Docker + OpenClaw + Telegram Bot environment used in Parts 1 and 2 ready.
- Even if you haven't taken Parts 1 and 2, I have structured it so that you can set up the minimum environment required for the multi-agent practice by following the โEnvironment Check Route A / Minimum Setup Onboarding Route Bโ included in Part 2.5.
- You will need a Gemini API key issued by Google AI Studio.
If you have any questions or get stuck while taking Part 2.5, please feel free to leave them on the Q&A board at any time.
Based on your feedback, we will continue to strengthen the practice examples and troubleshooting guides.
I hope this Part 2.5 serves as an opportunity to expand your OpenClaw environment from "one smart assistant" into a "small AI team with divided roles."
Thank you.




