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Duration 14 hours
Course Outline
Introduction to Multimodal AI
- Defining multimodal AI
- Industry-specific use cases
Prompt Engineering Basics
- Key principles for effective prompt design
- Understanding how AI models respond
- Identifying and preventing common errors
Optimizing Text-Based Prompts
- Structuring prompts for precise text output
- Adjusting responses for various contexts
- Managing ambiguity and bias in text inputs
Image Generation and Manipulation
- Directing style, layout, and visual elements
- Utilizing AI-based editing utilities
Audio and Speech Processing
- Producing speech via text prompts
- AI-enhanced audio improvement and synthesis
- Establishing voice-based AI interactions
Creating Video Content with AI
- Merging AI-generated text, visuals, and sound
- Post-editing and polishing AI-made video content
Multimodal AI Workflow Integration
- Real-world case studies and applications
Ethics and Best Practices
- Addressing AI bias and content moderation
- Privacy issues in multimodal AI systems
Recap and Future Directions
Requirements
- A solid understanding of AI models and their real-world uses
- Programming experience (Python is recommended)
- Experience with APIs and AI-driven processes
Target Audience
- AI researchers
- Multimedia creators
- Developers working with multimodal models
Testimonials (1)
Our trainer, Yashank, was incredibly knowledgeable. He modified the curriculum to match what we truly needed to learn, and we had a great learning experience with him. His understanding of the domain he was teaching was impressive; he shared insights from real experience and helped us solve actual problems we were facing in our work.
