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Overview
Throughout the course, students will explore practical applications of generative AI across various domains, such as content creation, image generation, and text synthesis. The curriculum includes hands-on projects where learners will use tools and frameworks like TensorFlow and PyTorch to build and fine-tune their own generative models.
Syllabus
What is Generative AI?
- A Brief History of AI
AI in the Workplace
- Human Involvement
- Major AI Players
Generative AI Plans
- Free vs. Paid
- Plans for Individuals vs. Plans for Business
- Data Privacy
Generative AI in Motion Graphics and Video Production
- Text to Text, Text to Image, Text to Video, Text to Audio, Text to 3D Model
- Developing a Workflow
- Research
- Ideation & Concept Generation
- Concept Art Creation: Mood/Inspiration Boards
- Scriptwriting
- Story Breakdowns & Shotlists
- Storyboarding
- Asset Generation & Cleanup
- Background Animation
Copyright & Legal Implications
- Confidentiality (Data Privacy)
- Copyright & Ownership of AI-Generated Content Liability
- Licensing & Permissions
Getting Started with Generative AI
- What are Prompts?
Prompt Frameworks/Prompt Engineering
- Example of a Prompt Framework
Generating Text
- Asking Questions
- Creating Prompts
- Continuous Chat & Follow Up Messages
Generating Images
- Visual Asset Generation
- Generating Images from Text Prompts
- Image Styles: Illustration vs. Photography
- Using Image References
Generating Audio
- Voiceover & Music Generation
- Trainable Voice Models
- Integrating Generated Assets into Projects
Generating Video & Animation
- Generating Video/Animation
- Integrating Generated Assets into Projects
Generating 3D Assets
- Generating 3D Models
- Integrating Generated Assets into Projects
Instructor
NobelDesktop
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