Elasticsearch with Python is a 18-hour training course by IT Genius Institute. ElasticSearch คือเครื่องมือค้นหาและวิเคราะห์ข้อมูลแบบกระจาย ที่มีพื้นฐานมาจาก Apache Lucene การรองรับภาษาต่างๆ ประสิทธิภาพที่สูง และเอกสาร JSON…
Training schedule
No public rounds are open right now — register your interest and we will contact you when the next round opens, or request an in-house session for your team.
Module 1: Introduction to Elasticsearch with Python
Introduction to Elasticsearch
Overview of the Elastic Stack
Elasticsearch architectures
Module 2: Getting started
Overview of installation options
Running Elasticsearch & Kibana in Elastic Cloud
Setting up Elasticsearch & Kibana on macOS & Linux
Setting up Elasticsearch & Kibana on Windows
Understanding the basic architecture
Inspecting the cluster
Sending queries with cURL
Sharding and scalability
Sharding
Understanding replication
Adding more nodes to the cluster
Overview of node roles
Module 3: Managing Documents with Python
Creating & deleting indices
Indexing documents
Retrieving documents by ID
Updating documents
Scripted updates
Upserts
Replacing documents
Deleting documents
Understanding routing
How Elasticsearch reads data
How Elasticsearch writes data
Understanding document versioning
Optimistic concurrency control
Update by query
Delete by query
Batch processing
Importing data with cURL
Module 4: Mapping & Analysis
Introduction to Mapping
Introduction to analysis
Using the Analyze API
Understanding inverted indices
Introduction to mapping
Overview of data types
How the "keyword" data type works
Understanding type coercion
Understanding arrays
Adding explicit mappings
Retrieving mappings
Using dot notation in field names
Adding mappings to existing indices
How dates work in Elasticsearch
How missing fields are handled
Overview of mapping parameters
Updating existing mappings
Reindexing documents with the Reindex API
Defining field aliases
Multi-field mappings
Index templates
Introduction to the Elastic Common Schema (ECS)
Introduction to dynamic mapping
Combining explicit and dynamic mapping
Configuring dynamic mapping
Dynamic templates
Mapping recommendations
Stemming & stop words
Analyzers and search queries
Built-in analyzers
Creating custom analyzers
Adding analyzers to existing indices
Updating analyzers
Module 5: Searching for Data
Introduction to searching
Introduction to term level queries
Searching for terms
Retrieving documents by IDs
Range searches
Prefixes, wildcards & regular expression
Querying by field existence
Introduction to full text queries
The match query
Introduction to relevance scoring
Searching multiple fields
Phrase searches
Leaf and compound queries
Querying with boolean logic
Query execution contexts
Boosting query
Disjunction max (dis_max)
Querying nested objects
Nested inner hits
Nested fields limitations
Module 6: Joining Queries
Introduction to Joining Queries
Add departments test data
Mapping document relationships
Adding documents
Querying by parent ID
Querying child documents by parent
Querying parent by child documents
Multi-level relations
Parent/child inner hits
Terms lookup mechanism
Join limitations
Join field performance considerations
Module 7: Controlling Query Results
A word on document types
Specifying the result format
Source filtering
Specifying the result size
Specifying an offset
Pagination
Sorting results
Sorting by multi-value fields
Filters
Module 8: Aggregations
Introduction to aggregations
Metric aggregations
Introduction to bucket aggregations
Document counts are approximate
Nested aggregations
Filtering out documents
Defining bucket rules with filters
Range aggregations
Histograms
Global aggregation
Missing field values
Aggregating nested objects
Module 9: Improving Search Results
Introduction to this section
Proximity searches
Affecting relevance scoring with proximity
Fuzzy match query (handling typos)
Fuzzy query
Adding synonyms
Adding synonyms from file
Highlighting matches in fields
Stemming
Frequently asked questions
Who is Elasticsearch with Python for, and what background is needed?
Built for ผู้ดูและระบบ · Database Administrator (DBA) Background you should have: พื้นฐานการออกแบบเว็บไซต์ด้วยภาษา HTML และ CSS · เข้าใจแนวคิด โครงสร้างของเทคโนโลยี Python Not sure the fit is right? Talk to our team on LINE @itgenius or call 02-570-8449.
How much does Elasticsearch with Python cost and how long does it run?
THB 12,500 (currently THB 11,250 on promotion). The course runs 18 hours. The fee covers course materials, lunch and refreshments throughout. Pay by bank transfer to the company account, confirm it on our payment page, and we can issue the receipt or tax invoice in your company's name.
Do I get a certificate?
Yes. Everyone who completes the course receives a Certificate of Completion from IT Genius Institute. Each certificate carries its own number, and anyone holding that number can verify it online on our certificate page, so you can add it to your portfolio or pass it to HR as evidence of training.
Where does the training take place, and is there an online option?
You can attend onsite at IT Genius Institute or arrange to join online, and we also run it as a private in-house session for your team. Ask about dates and venues on LINE @itgenius or call 02-570-8449.
What if I fall behind or miss a session — can I retake it?
Yes. You may retake the same course free of charge in a later round, under the institute's conditions. Tell our team which course and round you attended, and we will check it and offer you the rounds that still have seats. Ask us on LINE @itgenius or call 02-570-8449.
How do I enrol, or request a quotation for my company?
Enrol online with the registration form on this page. You can register several attendees at once and enter your tax ID and billing address for the tax invoice. Or request a company quotation straight from the quote button. For anything else call 02-570-8449 or reach us on LINE @itgenius.
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