WorkBuddy Education Full-Process Practical Course: Master AI Lesson Prep, Teaching Research, Homework Grading, No-Student Trial Teaching Coaching, and QuickForm Local Deployment

1. Course Introduction

An AI teaching and office-efficiency course built specifically for primary/secondary school and university teachers and education practitioners. It builds a complete learning system around platform basics, connectors, automation, custom Skill development, API calls, cloud storage, audio/video processing, image recognition, and local deployment. Starting from WorkBuddy's spaces, tasks, storage, operation modes, models and connectors, it gets you going fast through cases like paper visual summaries, automated tasks and CLI integration; then advances to Skill deployment and self-development, building teacher-specific tools such as literature download and organization, complex lesson-plan template filling, and knowledge cards, and using APIs for instructional design and paper assistance, AI image generation, mind maps, and smart homework grading. The course also covers TOS cloud storage, voice-timbre generation, classroom-recording processing, AI no-student trial-teaching coaching, speech recognition, AI auto-editing, image recognition, as well as QuickForm invocation and local deployment, helping teachers truly integrate AI into lesson prep, teaching research, grading, office work and classroom practice, building a reusable personal AI workflow and reducing repetitive mechanical work.

2. Who This Is For

1. Frontline teachers burdened by heavy daily lesson-prep work
2. Education workers who want to use AI to raise efficiency
3. Teaching researchers who often make lesson plans and courseware
4. Teachers who want to learn Skill and API applications
5. Zero-foundation learners who want to build an AI teaching workflow

3. What You Will Gain

1. Master WorkBuddy core features and operations
2. Independently build teacher-specific AI Skills
3. Master API and agent invocation methods
4. Achieve efficiency gains in audio/video, grading and teaching research
5. Build a personal AI teaching automation workflow

4. Course Catalog:

01. Course Preface

02. Session 1.1 - Getting to know WorkBuddy areas, storage, tasks and spaces

03. Session 1.2 - Getting to know WorkBuddy tasks, spaces, modes and models

04. Session 1.3 - Getting to know WorkBuddy connectors

05. Session 1.4 - Practice Case 1: removing the Feixiang teacher's placeholder

06. Session 1.5 - Practice Case 2: turning a paper into a visual summary

07. Session 1.6 - Advanced Case 1: the assistant's efficient work

08. Session 1.7 - Advanced Case 2: how to set up and use the automation feature

09. Session 1.8 - Advanced Case 3: connecting WorkBuddy to CLI

10. Session 2.1 - Pre-class Q&A

11. Session 2.2 - Built-in skills: deployment and 3D models

12. Session 2.3 - The image-hosting skill in the skill store

13. Session 2.4 - Making a skill: literature download and organization skill

14. Session 2.5 - Making a skill: filling complex templates for instructional design

15. Session 2.6 - Making a skill: knowledge cards skill

16. Session 3.1 - Pre-class Q&A and preparation

17. Session 3.2 - Beginner API: adding an API to an HTML page

18. Session 3.3 - Beginner API: the pen skill writing cases, instructional design, papers

19. Session 3.4 - Beginner API: the super image-generation skill

20. Session 3.5 - Advanced API: invoking a Coze agent to build a mind-map skill

21. Session 3.6 - Advanced API: invoking Coze programming to build a homework-grading skill

22. Session 4.1 - Creating a TOS bucket

23. Session 4.2 - Using the TOS bucket

24. Session 5.1 - Offline lecture experience sharing

25. Session 5.2 - Building an audio-generation skill

26. Session 5.3 - Practice 1: generating audio from a voice timbre

27. Session 5.4 - Practice 2: Voice Lab + data recovery

28. Session 5.5 - Building an audio-processing skill

29. Session 5.6 - Practice 1: classroom recording, no-student trial-teaching coaching skill

30. Session 5.7 - Practice 2: speech recognition lab

31. Session 5.8 - Practice 3: AI auto-editing video

32. Session 5.9 - Building an image-recognition skill

33. Session 5.10 - Image recognition lab

34. Session 6.1 - Pre-class experience sharing

35. Session 6.2 - Building a QuickForm-invocation skill

36. Session 6.3 - QuickForm CLI application practice

37. Session 6.4 - Preparing for QuickForm local deployment

38. Session 6.5 - Local deployment practice: Little Campus Observer

39. Session 6.6 - Key classroom summary