Building Multimodal AI Agents and Contextual Systems

AI agents are revolutionizing how complex tasks are automated, moving beyond simple single-prompt interactions to coordinated, multi-step workflows. This course provides a practical foundation in designing, building, and deploying sophisticated multi-agent systems, enabling you to create powerful, context-aware assistants capable of handling various data types. ### What you'll learn * Understand the core concepts of autonomous AI agents, including planning, memory, and tool integration. * Design effective multi-agent architectures for complex workflows and sequential task execution. * Apply Retrieval-Augmented Generation (RAG) patterns to provide agents with up-to-date, external contextual information. * Configure agents to handle multimodal inputs, specifically integrating text and image analysis capabilities. * Practice integrating agent systems into multi-server environments for scalable application deployment. This course begins with foundational definitions of agent components and roles, progresses through practical design patterns for communication and orchestration, and concludes with exercises on building and testing a contextual retrieval assistant. This course is designed for absolute beginners interested in applied AI development. No prior experience with agent frameworks or advanced AI concepts is required. Start building the next generation of intelligent systems today.