Elasticsearch Course for Beginners

Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations. ✏️ Course developed by @3CodeCampers ⭐️ Links ⭐️ Here is the link to the GitHub repository to get slides, notebooks and the source code for the final project: https://github.com/ImadSaddik/ElasticSearch_Python_Tutorial Link to the 3CodeCamp YouTube channel: https://www.youtube.com/@3CodeCampers Link to the official documentation: https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html Link to the starter project: https://www.elastic.co/search-labs/tutorials/search-tutorial/starter-project Link to the original APOD website: https://apod.nasa.gov/apod/archivepix.html Link to my universe hub: https://myuniversehub.com/ ⭐️ Contents ⭐️ (0:00:00) General introduction (0:03:34) Introduction (0:05:56) Elasticsearch installation process (0:09:02) Create an index (0:15:00) Index documents (0:22:13) Field data types (0:36:55) Delete documents (0:39:45) Get documents (0:42:35) Count documents (0:46:05) The exists API (0:49:26) The update API (0:57:21) The bulk API (1:04:40) The search API - Part 1 (1:10:26) The search API - Part 2 (1:21:40) The search API - Part 3 (1:28:54) Dense vectors (1:33:34) Embeddings (1:42:11) kNN search (1:52:01) Deep pagination (2:08:35) Ingest pipelines (2:23:32) Ingest processors (2:31