Course Overview

Multimodal AI is transforming modern industries by enabling systems to process and combine data from multiple sources such as text, images, audio, and video. This course provides a comprehensive understanding of multimodal AI technologies and their applications in building intelligent, AI-driven solutions across different business environments.

Over five days, participants will explore advanced AI techniques for integrating multiple data modalities into automated workflows and real-world applications. The course covers the fundamentals of text and image processing, along with advanced topics such as video analysis, speech recognition, and multimodal content generation.

Participants will gain hands-on experience working with advanced AI models including GPT-4o, CLIP, and DALL·E, while also learning workflow automation using OpenAI Assistants and LangChain. Through practical exercises and real-world projects, attendees will develop the skills required to build, manage, and deploy multimodal AI solutions for content management, automation, and intelligent data analysis.

Agenda

Day — 1 Introduction to Multimodal AI

• Introduction to ChatGPT and other Large Language Models (LLMs).
• Understanding multimodal AI and its impact across various industries.
• Exploring advanced AI techniques for text processing and workflow automation.
• Introduction to multimodal systems integrating text, image, and audio inputs.
• Reviewing real-world use cases of multimodal AI applications.

Day — 2 Workflow Automation

• Techniques for managing complex multimodal AI scenarios and workflows.
• Using OpenAI Assistants for custom function calls and workflow automation.
• Exploring real-world applications of multimodal AI across different industries.
• Understanding LangChain for workflows integrating text with image and other modalities.
• Discussion on challenges and limitations in multimodal workflow automation.

Day — 3 Image Analysis with AI

• Understanding the fundamentals of AI-based image processing and analysis.
• Exploring AI techniques for image recognition, object detection, and pattern identification.
• Practical introduction to models such as GPT-4o, CLIP, and DALL·E for image analysis tasks.
• Hands-on exercise on building an image analysis pipeline using multimodal AI techniques.
• Discussion on best practices for deploying image analysis solutions in business environments.

Day — 4 Video Content Analysis

• Introduction to video analysis and AI-driven video content automation.
• Exploring video processing techniques including frame analysis, scene detection, and object tracking.
• Understanding how multimodal AI models extract and interpret information from video content.
• Hands-on exercise on building and deploying a video content analysis system using advanced AI techniques.
• Discussion on challenges, limitations, and solutions in real-time video analysis systems.

Day — 5 Audio Analysis and Multimodal Integration

• Exploring speech recognition and audio synthesis techniques in AI systems.
• Understanding multimodal integration for AI-driven workflow automation.
• Hands-on exercise on creating an audio analysis system integrated with multiple data modalities.
• Collaborative project on building and deploying a complete multimodal AI solution using text, image, video, and audio.
• Final project presentations, feedback session, and recap of future applications of multimodal AI.

Learning Outcomes

At the end of the ChatGPT Advanced: Mastering Multimodal AI Integration course, participants will be able to:

• Understand the fundamentals of multimodal AI and multimodal system processes.
• Integrate advanced AI techniques into multimodal workflows and applications.
• Implement and optimize ChatGPT for handling text, image, video, and audio inputs.
• Conduct image analysis using AI models to identify objects, patterns, and contextual information.
• Perform video content analysis and information extraction using multimodal AI techniques.
• Analyze and synthesize audio inputs for intelligent automation and dynamic task execution.

Who Should Attend

This course is designed for professionals interested in multimodal AI integration and workflow automation, including:

• IT Professionals and Developers
• Data Scientists and AI Engineers
• Business Analysts and Decision-Makers
• Software Developers
• Product Managers
• Entrepreneurs and Business Leaders