LLMs in Multimodal Applications Training Course

Introduction to Multimodal Learning

• Overview of multimodal AI.
• Challenges in multimodal data processing.
• Benefits of multimodal LLMs.

Understanding Large Language Models

• Architecture of state-of-the-art LLMs.
• Training LLMs with multimodal data.
• Case studies: Successful multimodal LLM applications.

Processing Multimodal Data

• Data preprocessing techniques for text, image, and audio.
• Feature extraction and representation learning.
• Integrating multimodal data in LLMs.

Developing Multimodal LLM Applications

• Designing user interfaces for multimodal interaction.
• LLMs in virtual assistants and chatbots.
• Creating immersive experiences with LLMs.

Evaluating and Optimizing Multimodal Systems

• Performance metrics for multimodal LLMs.
• Optimization strategies for better accuracy and efficiency.
• Addressing bias and fairness in multimodal systems.

Hands-on Lab: Building a Multimodal LLM Project

• Setting up a multimodal dataset.
• Implementing a multimodal LLM for a specific use case.
• Testing and refining the system.

Summary and Next Steps