Multimodal AI Training in Kuala Lumpur, Malaysia

Foundations of Multimodal AI

• Session 1: Introduction to Multimodal AI

  • Overview of multimodal AI and its significance.
  • Applications across industries (e.g., healthcare, retail, media).
  • Tools and frameworks for multimodal AI development.

• Session 2: Multimodal Data Processing

  • Challenges in handling and integrating diverse data types.
  • Preprocessing techniques for text, images, audio, and video.

• Session 3: Architectures for Multimodal AI

  • Overview of state-of-the-art models (e.g., CLIP, DALL-E, GPT-4 Vision).
  • Techniques for aligning and fusing multiple modalities.

Advanced Applications and Deployment

• Session 4: Training and Optimizing Multimodal Models

  • Fine-tuning pre-trained models for multimodal tasks.
  • Addressing challenges in model training and performance.

• Session 5: Practical Applications and Case Studies

  • Use cases in e-commerce (e.g., product recommendations).
  • Applications in healthcare (e.g., diagnostics using image and text data).

• Session 6: Ethics, Evaluation, and Future Trends

  • Ethical considerations in multimodal AI deployment.
  • Evaluation metrics for multimodal systems.
  • Emerging trends and innovations in multimodal AI research.
  • Hands-on

This course ensures participants gain both theoretical insights and hands-on experience to confidently design, develop, and deploy multimodal AI solutions in diverse professional settings.