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Course Outline
Introduction to Generative AI with DeepSeek
- Overview of DeepSeek models for generative AI
- Understanding text, image, and multimedia generation
- Applications of AI in creative industries
Exploring Text Generation and Storytelling
- Using DeepSeek for AI-powered content creation
- Techniques for structuring and refining AI-generated text
- Building AI-assisted storytelling and narrative tools
AI-Powered Image and Art Generation
- DeepSeek Vision for image processing and synthesis
- Combining DeepSeek with other generative models (e.g., Stable Diffusion)
- Enhancing AI-generated images with style transfer and filters
Developing AI-Driven Creative Applications
- Integrating generative AI into creative workflows
- Building AI-assisted writing, design, and media tools
- Case studies of successful AI-driven creative projects
Optimizing AI-Generated Outputs
- Fine-tuning AI responses for consistency and coherence
- Controlling creativity and variability in AI models
- Addressing ethical considerations in AI-generated content
Scaling AI-Generated Content for Production
- Deploying generative AI applications in production
- Managing AI-generated content at scale
- Ensuring responsible AI use in creative industries
Future Trends in Generative AI
- Advancements in AI-generated media
- Trends in AI-assisted creativity and human-AI collaboration
- Building the future of generative AI applications
Summary and Next Steps
Requirements
- Experience with AI models and neural networks
- Proficiency in a programming language (e.g., Python, JavaScript)
- Basic understanding of creative AI concepts
Audience
- AI researchers exploring generative models
- Creative professionals leveraging AI for content generation
- Advanced developers working on AI-powered creative applications
14 Hours