Prompt Engineering for Multimodal AI Training Course
Multimodal AI is the next evolution of artificial intelligence, allowing models to process and generate content across text, images, audio, and video in a unified way.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI professionals who wish to enhance their prompt engineering skills for multimodal AI applications.
By the end of this training, participants will be able to:
- Understand the fundamentals of multimodal AI and its applications.
- Design and optimize prompts for text, image, audio, and video generation.
- Utilize APIs for multimodal AI platforms such as GPT-4, Gemini, and DeepSeek-Vision.
- Develop AI-driven workflows integrating multiple content formats.
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.
Course Outline
Introduction to Multimodal AI
- What is multimodal AI?
- How multimodal AI models work
- Use cases in various industries
Prompt Engineering Fundamentals
- Principles of effective prompt design
- Understanding AI response behavior
- Common mistakes and how to avoid them
Text-Based Prompt Optimization
- Structuring prompts for accurate text generation
- Fine-tuning responses for different contexts
- Handling 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
- An understanding of AI models and their applications
- Experience with programming (Python recommended)
- Familiarity with APIs and AI-driven workflows
Audience
- AI researchers
- Multimedia creators
- Developers working with multimodal models
Open Training Courses require 5+ participants.
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