Introduction to Qdrant (Vector Database) Using Python

About this course

Qdrant is an Open Source vector database with in-built vector similarity search engine. Qdrant is written in Rust and is proven to be fast and reliable even under high load in production environment. Qdrant provides convenient API to store, search and manage vectors along with the associated payload for the vectors.This course will provide you with solid practical Skills in Qdrant using its Python interface.  Before you begin, you are required to have basic knowledge onPython ProgrammingLinux CommandsDocker and Docker ComposeSome of the highlights of this course areAll lectures have been designed from the ground up to make the complex topics easy to understandAmple working examples demonstrated in the video lecturesDownloadable Python notebooks for the examples that were used in the coursePrecise and informative video lecturesQuiz at the end of every important video lecturesCovers a wide range of fundamental topics in Qdrant After completing this course, you will be able toInstall and work with Qdrant using PythonManage Collections in QdrantPerform vector search on vectors stored in Qdrant collection Filter the search resultsCreate and manage snapshotsUse Qdrant to build scalable real-world AI appsThis course will be updated periodically and enroll now to get lifelong access to this course!

Course objectives

• Provide solid practical skills in using Qdrant
• Simplify complex topics with clear explanations and examples