Multi Modal AI Combining Vision Text and Audio Course

Training Outlines

Introduction

In the rapidly evolving field of artificial intelligence, leveraging multiple data modalities is becoming increasingly vital for building comprehensive and efficient AI systems. This professional course, "Multi Modal AI Combining Vision, Text, and Audio," aims to equip participants with the knowledge and skills necessary to integrate these different modalities to create robust AI applications. Through a combination of theoretical insights and practical exercises, attendees will explore advanced techniques and state-of-the-art models that underpin multi-modal AI systems.

Objectives

• Understand the fundamentals of multi-modal AI and its applications.
• Learn to integrate vision, text, and audio data for AI development.
• Explore state-of-the-art models and techniques in multi-modal AI.
• Develop hands-on skills through practical projects and exercises.
• Apply multi-modal AI techniques to real-world problems and scenarios.

Course Outlines

Day 1: Introduction to Multi-Modal AI

• Overview of multi-modal AI and its significance.
• Understanding the synergy between vision, text, and audio modalities.
• Introduction to key concepts and terminologies.
• Exploring real-world applications and use cases.
• Setting up the development environment for the course.

Day 2: Multi-Modal Data Acquisition and Preprocessing

• Techniques for data acquisition from various sources.
• Preprocessing techniques for vision, text, and audio data.
• Data annotation and labeling for training multi-modal models.
• Challenges in handling diverse data types and resolutions.
• Hands-on session: Preparing a multi-modal dataset.

Day 3: Model Architectures for Multi-Modal AI

• Overview of multi-modal neural network architectures.
• Exploring attention mechanisms in multi-modal contexts.
• Combining convolutional and recurrent networks for multi-modality.
• Case study analysis of popular multi-modal models.
• Hands-on session: Building a simple multi-modal model.

Day 4: Training and Evaluation of Multi-Modal Models

• Strategies for effectively training multi-modal models.
• Cross-modal learning and feature fusion techniques.
• Evaluation metrics for multi-modal AI systems.
• Overcoming common challenges in model training and optimization.
• Hands-on session: Training a multi-modal AI model.

Day 5: Applications and Future Trends in Multi-Modal AI

• Exploring current and emerging applications of multi-modal AI.
• Innovative trends and future directions in the field.
• Ethical considerations and challenges in multi-modal AI.
• Building a capstone project utilizing vision, text, and audio.
• Course review and participant presentations of final projects.

Training Schedule

Below is the table of cities along with the respective dates for the upcoming training sessions of Multi Modal AI Combining Vision Text and Audio Course. Please review the schedule to find the most convenient option for you. You can also use the below search bar to type the city name and filter the results.