Building Multimodal AI Apps: Speech-to-Text and LLMs

Modern applications are moving beyond simple text. By integrating voice, image, and video processing capabilities, developers can create highly interactive and intelligent user experiences. This course provides a foundational understanding of multimodal Large Language Models (LLMs) and speech-to-text technologies. You will learn how to write code that interacts with AI models to transcribe audio, analyze visual data, and generate intelligent responses, transforming standard applications into powerful AI-driven tools. What you will learn: Understand the core concepts of multimodal AI and how models process different data types; Write code to integrate speech-to-text APIs for accurate audio transcription; Process and analyze images and video frames using modern LLM capabilities; Apply fundamental prompt engineering techniques tailored for multimodal inputs; Implement basic Retrieval-Augmented Generation (RAG) patterns for rich media; Build text-based scripts that orchestrate complex AI workflows seamlessly. The curriculum begins with essential AI terminology and foundational concepts before moving into practical API integration and data handling. You will progress through structured written lessons and coding snippets that build your confidence in handling various media types programmatically. This course is designed for beginner developers and fullstack engineers looking to enter the AI space with no prior machine learning experience required. Start reading today to unlock the potential of multimodal AI in your next development project.