As a developer who recently joined the OpenSearch team at NetApp Instaclustr, I found this course tremendously helpful. It covers fundamentals that matter day to day, like shard management and index optimization, while also framing topics from a customer perspective. Modern topics such as MCP and agents show how OpenSearch fits into current AI workflows. Altogether, it gave me a deeper understanding of OpenSearch and the use cases we support.

As someone new to OpenSearch, I found this course surprisingly approachable and very useful. I came in knowing little about vector search, neural pipelines, or RAG, and the structure made it easy to build understanding step by step. The course starts with the fundamentals of configuring and optimizing vector search, then moves into neural search pipelines, hybrid search, RAG optimization, and finally production cluster considerations. That progression worked well for me as a beginner — each chapter built on the previous one without assuming deep prior expertise. What helped most: Clear explanations of core concepts before diving into more advanced topics Practical focus across vector storage, hybrid search, and RAG Quizzes after each chapter that reinforced what I learned Coverage of production optimizations, which helped me see how these ideas apply beyond demos Even though the course goes into advanced areas, it stayed understandable for a newbie. I now feel much more confident exploring OpenSearch for AI-powered search use cases. Overall, this is a strong course for anyone who wants solid, practical knowledge into optimizing OpenSearch vector storage and search.

I learned a lot and the course was easy to follow along.

The video series helped walk me through understanding how to do advanced OpenSearch optimizations and better understand how the queries work. Definitely recommend!