Hybrid AI Search Workflows is an intermediate course designed for AI engineers, developers, and data scientists who want to build search systems that are both intelligent and factually reliable. While generative AI offers powerful reasoning, it can be prone to hallucination; traditional search is accurate but lacks contextual understanding. This course teaches you how to architect and implement hybrid workflows that get the best of both worlds, grounding powerful LLMs with verifiable data from classic search techniques.

You will move beyond basic prompting to design, evaluate, and optimize systems that balance performance and cost. Through hands-on labs, you will master techniques for tuning model parameters, designing cost-efficient hybrid architectures, and modularizing your code for scalable, production-ready CI/CD pipelines. By the end of this course, you will be equipped to build and deploy trustworthy AI search applications that deliver accurate, context-aware, and reliable answers.