Python for data Management II

The course focuses on Python workflows to manage scientific data through vector search, RAG and model serving.

Key topics

• Vector databases and semantic retrieval with Qdrant;
• RAG workflows using embedding and LLM APIs;
• Model serving with BentoML and integration into web applications.

Learning outcomes:

• Building and querying a vector database for scientific data;
  Implementing a simple RAG pipeline;
  Exposing and integrating a machine-learning model through an inference API.