Multimodal AI Essentials - Merging Text, Image, and Audio for Next-Generation AI Application

Course Outline
Multimodal AI Essentials: Introduction
Topics
1.1 Overview of Multimodal AI Concepts
1.2 Types of Data in Multimodal Systems
1.3 Building a Voice-to-Voice App
Topics
2.1 Understanding VQA: Concepts and Architecture
2.2 Fusing Modalities to Perform VQA
2.3 Blending Modalities to Perform VQA
Topics
3.1 Introduction to Diffusion Models
3.2 Hands-On: Implementing Diffusion Models with DreamBooth
Topics
4.1 Designing Multimodal AI Systems
4.2 Fine-Tuning a Text-to-Speech Model with T5
4.3 Building Visual Agents
Topics
5.1 Evaluating Multimodal Models: Accuracy and Performance
5.2 Bias and Ethics in Multimodality
Topics
6.1 Extending Multimodal Systems with Advanced Techniques
6.2 Future Trends and Innovations in Multimodal AI
Multimodal AI Essentials: Summary