Master Multi-Vector Search With Qdrant
Blog post from Qdrant
Qdrant's Multi-Vector Search Course, created by Kacper Ćukawski, addresses the need for a structured, hands-on resource for implementing advanced multi-vector retrieval systems in production environments. This free and advanced course is specifically designed for machine learning, backend, and search engineers who are already familiar with vector search fundamentals and seek to master multi-vector search techniques. The course is divided into four comprehensive modules, covering setup, text multi-vectors, multi-modal search, and optimization and evaluation, each with video lessons and practical exercises using Google Colab notebooks. Participants who complete the course and pass the certification exam can earn a Qdrant Multi-Vector Search certificate, demonstrating their ability to design and optimize multi-vector retrieval pipelines. Additionally, the first 20 individuals to achieve certification and share their accomplishment on LinkedIn with the hashtag #QdrantCertified will receive free Qdrant swag. The course is self-paced and encourages community interaction via a dedicated Discord channel.