- Basic understanding of AI and machine learning concepts
- Familiarity with UI/UX design principles
- Some experience with programming (Python preferred)
Audience
- UI/UX designers
- Product managers
- AI researchers
Human-AI collaboration with multimodal interfaces is transforming the way people interact with intelligent systems by integrating various communication modalities, such as speech, gestures, eye tracking, and visual elements.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level UI/UX designers, product managers, and AI researchers who wish to enhance user experiences through multimodal AI-powered interfaces.
By the end of this training, participants will be able to:
- Understand the fundamentals of multimodal AI and its impact on human-computer interaction.
- Design and prototype multimodal interfaces using AI-driven input methods.
- Implement speech recognition, gesture control, and eye-tracking technologies.
- Evaluate the effectiveness and usability of multimodal systems.
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 Multimodal Interfaces
- What are multimodal interfaces?
- Benefits and challenges of multimodal interactions
- Real-world applications in various industries
Multimodal AI and Human-Computer Interaction
- Understanding human-centered AI design
- Key AI technologies powering multimodal interfaces
- Psychological and cognitive considerations in human-AI collaboration
Speech Recognition and Natural Language Processing (NLP)
- Speech-to-text and text-to-speech technologies
- Using OpenAI's Whisper or Mozilla DeepSpeech
- Improving AI-driven voice interactions
Gesture Recognition and Motion Tracking
- Understanding hand tracking and body gestures
- Implementing gesture control in UI design
- Hands-on with open-source gesture recognition libraries
Eye Tracking and Gaze-Based Interaction
- Introduction to eye-tracking technology
- Use cases in accessibility and adaptive interfaces
- Developing gaze-based input systems
Multimodal Fusion: Integrating Multiple Input Methods
- How AI combines speech, gestures, and vision
- Building adaptive and personalized AI interactions
- Best practices for seamless multimodal experiences
Prototyping and Implementing Multimodal Interfaces
- Designing user-friendly AI-powered interfaces
- Prototyping multimodal interactions with Figma and AI tools
- Developing real-world applications using Python and AI frameworks
Testing and Evaluating Multimodal Interfaces
- Usability testing methodologies for multimodal AI
- Measuring user experience and satisfaction
- Refining and optimizing AI-driven interactions
Future Trends in Human-AI Collaboration
- Advancements in multimodal AI and deep learning
- Emerging trends in human-computer interaction
- The role of AI in the future of user experience
Summary and Next Steps
United Arab Emirates - Human-AI Collaboration with Multimodal Interfaces
Qatar - Human-AI Collaboration with Multimodal Interfaces
Egypt - Human-AI Collaboration with Multimodal Interfaces
Saudi Arabia - Human-AI Collaboration with Multimodal Interfaces
South Africa - Human-AI Collaboration with Multimodal Interfaces
Brasil - Human-AI Collaboration with Multimodal Interfaces
Canada - Human-AI Collaboration with Multimodal Interfaces
中国 - Human-AI Collaboration with Multimodal Interfaces
香港 - Human-AI Collaboration with Multimodal Interfaces
澳門 - Human-AI Collaboration with Multimodal Interfaces
台灣 - Human-AI Collaboration with Multimodal Interfaces
USA - Human-AI Collaboration with Multimodal Interfaces
Österreich - Human-AI Collaboration with Multimodal Interfaces
Schweiz - Human-AI Collaboration with Multimodal Interfaces
Deutschland - Human-AI Collaboration with Multimodal Interfaces
Czech Republic - Human-AI Collaboration with Multimodal Interfaces
Denmark - Human-AI Collaboration with Multimodal Interfaces
Estonia - Human-AI Collaboration with Multimodal Interfaces
Finland - Human-AI Collaboration with Multimodal Interfaces
Greece - Human-AI Collaboration with Multimodal Interfaces
Magyarország - Human-AI Collaboration with Multimodal Interfaces
Ireland - Human-AI Collaboration with Multimodal Interfaces
Luxembourg - Human-AI Collaboration with Multimodal Interfaces
Latvia - Human-AI Collaboration with Multimodal Interfaces
España - Human-AI Collaboration with Multimodal Interfaces
Italia - Human-AI Collaboration with Multimodal Interfaces
Lithuania - Human-AI Collaboration with Multimodal Interfaces
Nederland - Human-AI Collaboration with Multimodal Interfaces
Norway - Human-AI Collaboration with Multimodal Interfaces
Portugal - Human-AI Collaboration with Multimodal Interfaces
România - Human-AI Collaboration with Multimodal Interfaces
Sverige - Human-AI Collaboration with Multimodal Interfaces
Türkiye - Multimodal AI Arayüzleri ile İnsan-Yapay Zeka İlişkileri
Malta - Human-AI Collaboration with Multimodal Interfaces
Belgique - Human-AI Collaboration with Multimodal Interfaces
France - Human-AI Collaboration with Multimodal Interfaces
日本 - Human-AI Collaboration with Multimodal Interfaces
Australia - Human-AI Collaboration with Multimodal Interfaces
Malaysia - Human-AI Collaboration with Multimodal Interfaces
New Zealand - Human-AI Collaboration with Multimodal Interfaces
Philippines - Human-AI Collaboration with Multimodal Interfaces
Singapore - Human-AI Collaboration with Multimodal Interfaces
Thailand - Human-AI Collaboration with Multimodal Interfaces
Vietnam - Human-AI Collaboration with Multimodal Interfaces
India - Human-AI Collaboration with Multimodal Interfaces
Argentina - Human-AI Collaboration with Multimodal Interfaces
Chile - Human-AI Collaboration with Multimodal Interfaces
Costa Rica - Human-AI Collaboration with Multimodal Interfaces
Ecuador - Human-AI Collaboration with Multimodal Interfaces
Guatemala - Human-AI Collaboration with Multimodal Interfaces
Colombia - Human-AI Collaboration with Multimodal Interfaces
México - Human-AI Collaboration with Multimodal Interfaces
Panama - Human-AI Collaboration with Multimodal Interfaces
Peru - Human-AI Collaboration with Multimodal Interfaces
Uruguay - Human-AI Collaboration with Multimodal Interfaces
Venezuela - Human-AI Collaboration with Multimodal Interfaces
Polska - Human-AI Collaboration with Multimodal Interfaces
United Kingdom - Human-AI Collaboration with Multimodal Interfaces
South Korea - Human-AI Collaboration with Multimodal Interfaces
Pakistan - Human-AI Collaboration with Multimodal Interfaces
Sri Lanka - Human-AI Collaboration with Multimodal Interfaces
Bulgaria - Human-AI Collaboration with Multimodal Interfaces
Bolivia - Human-AI Collaboration with Multimodal Interfaces
Indonesia - Human-AI Collaboration with Multimodal Interfaces
Kazakhstan - Human-AI Collaboration with Multimodal Interfaces
Moldova - Human-AI Collaboration with Multimodal Interfaces
Morocco - Human-AI Collaboration with Multimodal Interfaces
Tunisia - Human-AI Collaboration with Multimodal Interfaces
Kuwait - Human-AI Collaboration with Multimodal Interfaces
Oman - Human-AI Collaboration with Multimodal Interfaces
Slovakia - Human-AI Collaboration with Multimodal Interfaces
Kenya - Human-AI Collaboration with Multimodal Interfaces
Nigeria - Human-AI Collaboration with Multimodal Interfaces
Botswana - Human-AI Collaboration with Multimodal Interfaces
Slovenia - Human-AI Collaboration with Multimodal Interfaces
Croatia - Human-AI Collaboration with Multimodal Interfaces
Serbia - Human-AI Collaboration with Multimodal Interfaces
Bhutan - Human-AI Collaboration with Multimodal Interfaces
Nepal - Human-AI Collaboration with Multimodal Interfaces
Uzbekistan - Human-AI Collaboration with Multimodal Interfaces