AI Comic-Drama Full Workflow Practical Course – 36 Systematic Lessons, Complete Closed Loop from AI Image Generation to Douyin Paid Monetization
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📅 Release Date:
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September 2, 2026
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📚 Course Type:
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AI Comic-Drama Production
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👥 Target Audience:
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Side-Hustle Beginners, Self-Media Creators, Short Video Bloggers, Comic-Drama Track Practitioners
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《AI Comic Drama Full-Process Practical Course》is a systematic practical course designed for zero-foundation students, covering production from scratch, batch output, and full-process monetization. The complete set of 36 refined lessons covers all core gameplay, practical techniques, and monetization logic in the AI comic drama niche. The course starts with niche awareness and monetization logic, first helping students fully grasp the core definition of AI comic dramas and diverse monetization methods, and master the full process of newbie account setup, novel sourcing, copyright avoidance, and downloading and copying full-set materials and other early-stage core issues; then it goes deep into core AI creation techniques, including the full practical process of AI novel rewriting, multi-style voiceover, voice cloning, batch voiceover, emotional audio tuning, and subtitle alignment. This is a practical guide to help students quickly enter the AI comic drama niche. The course deeply breaks down the underlying logic of AI, teaching step by step character finalization, multi-model selection, and the use of online image-generation tools, solving industry pain points such as image watermarks, blurry image quality, and scene extraction. Students will unlock three AI video-production methods, Jimeng voice consistency techniques, and batch production software practice, achieving fully automatic batch output of copy, storyboards, characters, scenes, and videos. It also covers professional video editing, camera-movement opening production, and high-click-through-rate cover design, with exclusive teaching of Douyin paid upload monetization methods, truly building a complete closed-loop system of pre-production preparation → material processing → AI creation → refined finished video → publishing and monetization → diversified income growth.\
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Niche Awareness
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- 1.What Is an AI Comic Drama
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- 2.AI Comic Drama Monetization Methods
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- 3.Complete Process Outline for Making Comic Dramas
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- 4.Preparation for Newbies to Start an Account
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Asset Preparation
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- 5.How to Find Novels and Resolve Copyright Issues
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- 6.Quickly Download and Copy Full Novel Sets
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Copywriting and Voiceover
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- 7.How to Use AI to Help Us Revise Novel Copy
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- 8.Basic Narration Voiceover Techniques
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- 9.How to Clone a Desired Voice
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- 10.How to Batch Voiceover
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- 11.How to Make Voices More Emotional After Voiceover: Audio Tuning Section
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- 12.How to Align Subtitles After Audio Tuning: Free Subtitle Recognition in CapCut
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AI Image Generation
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- 13.Underlying Logic of AI Usage
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- 14.How to Generate Characters and Finalize Characters
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- 15.Other models: usage and selection
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- 16.Online image-generation software roundup
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- 17.How to Handle Image Watermarks
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- 18.Techniques to Make Images High-Definition
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- 19.How to generate and extract scenes
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[AI出片]
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- 20.First method to produce video
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- 21.Second method to produce video
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- 22.Third method to produce video
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- 23.Keeping Jimeng voices consistent
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- 24.Batch video-making software usage and walkthrough
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- 25.How to batch-output copy, storyboards, character, and scene images
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- 26.How to batch-output images and videos
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[Post-Production]
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- 27.How to edit finished videos (Part 1)
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- 28.How to edit finished videos (Part 2)
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- 29.How to make attractive covers
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- 30.Notes when publishing works
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- 31.Video Camera Movements and Adding an Opening Intro
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- 32.Other monetization methods beyond comic dramas
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[Monetization Advanced]
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- 33.How to upload finished comic dramas to Douyin for paid access
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- 34.Beginners' direction, production approach, and conclusion
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- 35.How to make lifelike comic-drama videos
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- 36.How to generate weapons and props
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💡 Learning Tip:Content reflects industry practices at time of publication. Please refer to the latest platform rules when learning.
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