Building Multimodal Generative AI Applications

AI is no longer limited to just reading and writing text. Modern applications must process speech, images, and video simultaneously to deliver truly intelligent, real-world experiences. In this course, you will learn how to connect different data types—text, audio, and visual inputs—to build cohesive, multimodal generative AI systems. You will understand how these models communicate, align different media formats, and work together to solve complex problems. By focusing on practical written design patterns and structural concepts, you will gain the confidence to architect applications that can hear, see, and speak. What you'll learn: - Understand the core concepts of multimodal AI, including how models process text, image, and audio inputs simultaneously. - Apply speech-to-text models like Whisper to transcribe and analyze audio data. - Explore image and video generation concepts using modern generative models like Granite. - Implement multimodal prompt engineering techniques to guide models across different media types. - Manage multimodal embeddings and vector databases to store and retrieve cross-media information. - Design basic orchestration workflows to connect language models with vision and speech tools. The journey begins with foundational definitions of multimodal architectures before moving into step-by-step written guides on audio processing, computer vision integration, and cross-modal orchestration. You will practice these concepts through written code walkthroughs and conceptual design exercises. This course is designed for beginner developers, technical product managers, and AI enthusiasts who want to understand the next generation of AI systems, requiring only basic programming familiarity. Start reading today to unlock the potential of multi-sensory artificial intelligence.