DeepSeek: Generative AI and Creative Applications

• 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

DeepSeek models, including DeepSeek-R1 and DeepSeek-V3, offer powerful generative AI capabilities for content creation, art generation, and storytelling.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI researchers, creative professionals, and advanced developers who wish to explore generative AI techniques, implement AI-driven creative workflows, and develop applications using DeepSeek models.

By the end of this training, participants will be able to:

• Understand the generative AI capabilities of DeepSeek models.
• Generate text, images, and creative content using AI.
• Optimize AI-generated outputs for different creative applications.
• Develop AI-powered tools for storytelling, design, and media.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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