Within this course, you’ll learn about how PostgreSQL creates and uses inverted indexes for JSON and natural language content. We will use various sources of data for our databases, including access to an online API and spidering its data and storing the data in a JSON column in PostgreSQL. Students will explore how full-text inverted indexes are structured. Students will build their own inverted indexes and then make use of PostgreSQL built-in capabilities to support full-text indexes.
JSON and Natural Language Processing in PostgreSQL
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JSON and Natural Language Processing in PostgreSQL
This course is part of PostgreSQL for Everybody Specialization
Instructor: Charles Russell Severance
8,820 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.6
(125 reviews)
Intermediate level
Recommended experience
16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Compare Python, PostgreSQL, and JSON.
Index and retrieve natural language text and JSON data; access API data and store it in a database.
Create a GIN-based text[] reverse index and ts_vector index; build a search engine in PostgreSQL.
Skills you'll gain
Details to know
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Assessments
2 assignments
Taught in English
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This course is part of the PostgreSQL for Everybody Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
In this first week, we introduce you to the course and its main focus: text and JSON.
What's included
9 videos5 readings4 app items
In this week, we'll look at GIN-based inverted indexes and ts_vector() and ts_query() functions.
What's included
7 videos1 reading1 assignment2 app items
This week is all about connecting and comparing Python and PostgreSQL.
What's included
10 videos2 readings2 app items
In this final week, we'll focus primarily on JSON and its functions.
What's included
11 videos2 readings1 assignment1 app item
Instructor
Instructor ratings
4.1 (19 ratings)Offered by
Recommended if you're interested in Software Development
University of Michigan
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4.6
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