AI video creation has now become a mainstream track for content monetization and self-media income, but the vast majority of beginners face many pain points: they only know how to simply apply templates, lack understanding of story planning and storyboard design, and produce videos that are empty and lack texture; they do not understand the underlying logic of various AI models and tools, and random operations frequently cause issues such as distorted images, incorrect proportions, and voiceover errors; prompt writing is disorganized and cannot precisely control visual style or camera effects, resulting in severely homogenized output; they only know basic operations of a single tool and cannot perform multi-platform, multi-model collaborative creation, making it difficult to produce diversified videos such as digital humans, ancient-style blockbusters, and e-commerce recommendations; they do not know batch creation techniques, resulting in extremely low production efficiency and an inability to achieve account matrix mass-production monetization.

This AI video practical implementation course focuses on hands-on practice with real cases, designed specifically for complete beginners. It abandons obscure and boring theoretical piles, centers entirely on practical implementation, and fully walks through the entire AI video creation chain from creative planning, material production, generation and editing to batch output. The course systematically covers practical cases from AI introductory cognition and mainstream tool operation to advanced prompt engineering, cinematic camera language scheduling, and then digital human production, e-commerce recommendations, animation effects, and other popular tracks, helping students build a complete AI video creation knowledge system.

The course specially includes a large number of "beginner follow-along" segments, allowing students to follow the instructor step by step through the entire process from story planning, storyboard design, and asset production to video generation and editing. At the same time, the course deeply breaks down the core functions and linkage techniques of mainstream AI platforms such as Codex, Jimeng, Seedance, Doubao, and Gemini, teaching everyone how to build automated workflows and achieve batch AI video output. Whether you want to run a self-media account, do e-commerce sales, take orders to make money, or simply want to master a cutting-edge skill, this course can provide a complete solution from 0 to 1, helping you achieve skill monetization in the field of AI video creation.

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• 1.入门导学课
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• 2.Designed for complete zero-foundation beginners
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• 3.如何策划剧情
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• 4.Case story and storyboard design
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• 5.案例资产设计
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• 6.Case video generation and editing
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• 7.E-commerce recommendation video production
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• 8.What we mainly use Codex for
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• 9.Codex installation and registration
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• 10.Full walkthrough of Codex story marketing
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• 11.The principles and boundaries of what Codex can do for video
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• 12.Codex audio and video plugin dependency explained
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• 13.Codex graphic and dynamic information video production
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• 14.Codex talking-head presenter packaging video production
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• 15.Codex visual design video production
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• 16.How to integrate RH open-source models into Codex
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• 17.Using Codex to design AI video automation workflows
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• 18.Low-cost batch production of clothing showcase videos
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• 19.Solving AI video audio generation errors
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• 20.RH infinite canvas image-to-video creation method
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• 21.Case study breakdown of ancient painting restoration
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• 22.Shaw Brothers style snow mountain fox rescue series tutorial
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• 23.Breakdown of film and TV character styling recreation
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• 24.Using Nanobanana on the RH platform
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• 25.Using Seedance to create hyper-realistic digital humans
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• 26.Download Jimeng watermark-free avatar videos (Windows version)
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• 27.Solving Jimeng real-person generation issues
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• 28.Solving AI image generation object proportion control issues
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• 29.(Open-source version) Live-action + AI generation fusion Animate move explained
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• 30.Understanding the relationship between models and platforms
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• 31.Three methods of image-to-video
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• 32.How to use the Jimeng platform
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• 33.How to use Doubao
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• 34.How to write AI image prompts
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• 35.Applications of AI graphic and text layout
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• 36.Editing and modifying AI images
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• 37.Prompt engineering — prompt control determines image quality
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• 38.Prompt engineering — the underlying principles of AI image generation
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• 39.Prompt engineering — what is prompt engineering
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• 40.Prompt engineering — the six-dimensional composition system of prompts
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• 41.Mastering the 4 core control dimensions of video prompts
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• 42.Analyzing 5 key transition techniques for AI video first and last frames
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• 43.Beginner follow-along — Ghibli short animation
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• 44.Beginner follow-along — Northeast China comedy skit
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• 45.Which platforms use GPT Img2
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• 46.GPT Img2 character design
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• 47.GPT Img2 graphic and text popular science
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• 48.GPT Img2 visual communication
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• 49.GPT Img2 product showcase and other cases
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• 50.What should we learn when technology changes rapidly
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• 51.Using the Seedance series of tools
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• 52.Video replication
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• 53.Video editing
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• 54.Prompt key points 1
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• 55.Prompt key points 2
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• 56.Multi-reference application of images and text
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• 57.Getting to know Gemini and Nanobanana
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• 58.Mastering the basic writing method of multi-grid storyboards
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• 59.Multi-grid storyboard reorganization
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• 60.Mastering Gemini image editing features
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• 61.Two open-source free digital human solutions
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• 62.Using workflows to create hyper-realistic digital humans
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• 63.Talking-head digital human production process (Banana + Jimeng)
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• 64.Hyper-realistic Vlog digital human production method (Banana + Veo/Jimeng)
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• 65.Camera movement — directing shots like a film director
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• 66.Shot sizes — controlling visual tension
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• 67.Camera angles — creating multi-dimensional visual expression
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• 68.Introduction to basic tools
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• 69.Quickly understand the logic of AI image prompts
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• 70.Breaking down the DNA structure of prompts 1
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• 71.Breaking down the DNA structure of prompts 2
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• 72.Essential professional vocabulary concepts in prompts
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• 73.Prompt reverse-engineering + batch writing — quickly producing high-quality visuals
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• 74.Efficiently improving prompt writing skills
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• 75.Writing prompts like chatting — natural language image generation techniques
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• 76.Three batch generation methods — multiplying your creative efficiency
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• 77.Using batch generation to master AI video
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• 78.Essential AI image editing skills — erasing, outpainting, inpainting
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• 79.Essential AI image editing skills — style transfer, reference, blending
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• 80.Case 1: Using AI-generated music to match visuals
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• 81.Case 2: Color grading and Jimeng storyboard splitting case
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• 82.Case 3: Classical poetry production tutorial
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• 83.Case 4: Reverse-engineering + Jimeng reference image generation
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• 84.Case 5: Fujifilm-style beach girl case tutorial
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• 85.Case 14: Video batch reverse-engineering of wind sounds case tutorial
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• 86.Case 7: Creating a Car Commercial Blockbuster with GPT5+VEO3
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💡 Learning Tip:Content reflects industry practices at time of publication. Please refer to the latest platform rules when learning.