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Course Outline
Introduction to Multimodal AI
- Defining multimodal AI.
- How multimodal AI models function.
- Industry use cases.
Prompt Engineering Fundamentals
- Principles of effective prompt design.
- Understanding AI response behavior.
- Common pitfalls and how to avoid them.
Text-Based Prompt Optimization
- Structuring prompts for accurate text generation.
- Fine-tuning responses for various contexts.
- Addressing ambiguity and bias in text prompts.
Image Generation and Manipulation
- Optimizing prompts for AI-generated images.
- Controlling style, composition, and elements.
- Working with AI-powered editing tools.
Audio and Speech Processing
- Generating speech from text-based prompts.
- AI-driven audio enhancement and synthesis.
- Creating voice interactions with AI.
Video Content Creation with AI
- Generating video clips using AI prompts.
- Combining AI-generated text, images, and audio.
- Editing and refining AI-created video content.
Integrating Multimodal AI in Workflows
- Combining text, image, and audio outputs.
- Building automated AI-driven content pipelines.
- Case studies and real-world applications.
Ethical Considerations and Best Practices
- AI bias and content moderation.
- Privacy concerns in multimodal AI.
- Ensuring responsible AI use.
Summary and Next Steps
Requirements
- Understanding of AI models and their applications.
- Experience with programming (Python is recommended).
- Familiarity with APIs and AI-driven workflows.
Audience
- AI researchers.
- Multimedia creators.
- Developers working with multimodal models.
14 Hours
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.
