Search: Teaching the Fundamentals

  • Reducing busy work. We tried to minimize busy work in the projects, but we still saw a lot of unnecessary pain in setting up the ingestion and LTR pipelines. Experience is the best teacher, and we hope those who felt this pain will take solace in knowing that future students will benefit from their experience.
  • Covering dense neural retrieval. We taught students how to use embeddings for content and query understanding, but we only touched on vector-based methods for indexing and retrieving content. We know that many students were hoping for more, as evidenced by the popularity of a community talk that Dmitry Kan presented on the topic.
  • Supporting beginners. We pitched the course as having no prerequisites other than basic Python programming. But the course attracted students with a very wide range of backgrounds, and as a result we struggled to establish a pace that worked for everyone. In retrospect, it’s clear that beginners would have benefited from more support.
  • Search Fundamentals: a 2-week introductory course intended for people who have no previous experience working with search.
  • Search with Machine Learning: a 4-week course that assumes a background (e.g. basics of indexing, ranking and aggregations) in Search Fundamentals and will cover advanced topics like dense neural retrieval. This course requires certification in Search Fundamentals or equivalent experience as a prerequisite.

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