Master Elasticsearch fundamentals and practical applications in this 5-hour comprehensive video course suitable for beginners using any programming language, with Python demonstrations. Begin with core concepts including index management, document storage, text analysis, pipeline creation, and search functionality, then explore advanced features like semantic search and embeddings. Apply your knowledge by building a real-world website using the Astronomy Picture of the Day (APOD) dataset, implementing essential features such as data cleaning pipelines, tokenization, pagination, and aggregations. Access complete course materials including slides, notebooks, and source code through the provided GitHub repository. Progress through detailed modules covering installation, API usage, vector operations, data streams, analyzers, and SQL integration, culminating in a hands-on final project that reinforces all learned concepts.
Overview
Syllabus
General introduction
Introduction
Elasticsearch installation process
Create an index
Index documents
Field data types
Delete documents
Get documents
Count documents
The exists API
The update API
The bulk API
The search API - Part 1
The search API - Part 2
The search API - Part 3
Dense vectors
Embeddings
kNN search
Deep pagination
Ingest pipelines
Ingest processors
Filters in depth
SQL search API
Time series data stream
Analyzers
The synonyms API
Common options
Change the heap size
Final project - Part 0
Final project - Part 1
Final project - Part 2
Final project - Part 3
Final project - Part 4
Final project - Part 5
Final project - The end
Conclusion
Taught by
freeCodeCamp.org
