Ready to level up your GenAI skills? Step into the exciting world of multimodal AI, where language, images, and speech come together to build smarter, more interactive applications.



Build Multimodal Generative AI Applications
This course is part of IBM RAG and Agentic AI Professional Certificate


Instructors: Hailey Quach
Included with
Recommended experience
What you'll learn
Build the job-ready skills you need to build multimodal generative AI applications in just 3 weeks
Understand the fundamental concepts and challenges in multimodal AI, including the integration of text, speech, images, and video
Build multimodal AI applications using state-of-the-art models and frameworks such as IBM’s Granite, Meta’s Llama, OpenAI’s Whisper, DALL·E and Sora
Develop multimodal AI solutions, including chatbots and image/video generation models, using IBM watsonx.ai, Hugging Face, Flask and Gradio
Skills you'll gain
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May 2025
6 assignments
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There are 3 modules in this course
This module provides an in-depth introduction to multimodal AI, focusing on how AI systems process and integrate multiple data types, including text, speech, and images. You will explore core concepts and some of the challenges you will face in multimodal AI, gaining foundational skills with text and speech processing techniques. Through hands-on labs, you will apply AI-powered storytelling, speech-to-text transcription, and text-to-speech synthesis to real-world applications, such as AI-generated audiobooks and automated meeting assistants.
What's included
4 videos2 readings2 assignments2 app items6 plugins
This module explores how AI processes generate visual data by integrating images and videos with text. You will examine text-to-image/image-to-text and text-to-video/video-to-text models, image captioning, and the fusion techniques necessary for effective multimodal AI systems. Through hands-on labs, you will apply state-of-the-art models like DALL·E and Sora to generate images and videos from text prompts. Additionally, you will implement an image captioning system using Meta’s Llama 4, gaining practical experience in combining vision and language models for real-world applications.
What's included
2 videos1 reading2 assignments2 app items3 plugins
The final module explores advanced multimodal AI applications, integrating image, text, and retrieval-based systems to build innovative solutions. You will dive into multimodal retrieval and search, multimodal Question Answering (QA), and chatbots, learning how cross-modal retrieval techniques enhance search engines and recommendation systems. Additionally, you will learn how integrating visual and textual data improves chatbot interactions. Through hands-on labs, you will build fully functional web applications with multimodal capabilities using Flask, applying state-of-the-art models and frameworks.
What's included
3 videos3 readings2 assignments2 app items1 plugin
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Frequently asked questions
Skills in multimodal generative AI, where systems integrate text, speech, images, and video, are in high demand for roles such as AI developer, machine learning engineer, multimodal AI researcher, and full-stack developer specializing in AI-powered user experiences.
Not necessarily. If you’re a Python developer, you can start building with generative AI using tools like IBM watsonx.ai, Flask, and Gradio—no advanced ML background required.
Multimodal AI apps go beyond typical app development by incorporating multimodal large language models (MLLMs) and media-based inputs like speech, images, and video. You’ll still use familiar tools like Python, Flask and Gradio, but you’ll also learn to integrate and orchestrate models for tasks like transcription, image generation, and AI-powered storytelling.
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Financial aid available,