Qdrant Academy Launches with Qdrant Essentials Course

Qdrant Academy has launched its new learning site with the introduction of the Qdrant Essentials course, aimed at developers, data scientists, and engineers to facilitate the building of real-world vector search systems. The course offers a free, self-paced, comprehensive learning experience that covers the fundamentals of vector search, embeddings, indexing, filtering, hybrid search, and scaling, with practical applications in AI systems such as retrieval-augmented generation and recommendation engines. By combining theoretical knowledge with practical exercises and examples, the course aims to reduce onboarding time, improve search architecture quality, and prepare teams for scalable, production-ready retrieval systems. The Qdrant Essentials course includes videos, guides, code examples, and exercises organized into modules, and is supported by a range of ecosystem partners who contribute collaborative lessons. Participants are encouraged to engage with the course through the Qdrant Cloud account and the Discord community, with the opportunity to get certified, as Qdrant Academy plans to expand with more courses in the future.

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