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University of California, Davis - SQL for Data Science 

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SQL for Data Science
 at 
Coursera 
Overview

Master SQL skills to analyze, manipulate, and extract insights from data, essential for data science and business intelligence

Duration

15 hours

Mode of learning

Online

Difficulty level

Beginner

Official Website

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Credential

Certificate

SQL for Data Science
 at 
Coursera 
Highlights

  • Earn a shareable career certificate
  • Develop job-relevant skills with hands-on projects
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Financial aid is available
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SQL for Data Science
 at 
Coursera 
Course details

Skills you will learn
Who should do this course?

Data scientists, analysts, and business intelligence professionals

What are the course deliverables?
  • Identify a subset of data needed from a column or set of columns and write a SQL query to limit to those results

  • Use SQL commands to filter, sort, and summarize data

  • Create an analysis table from multiple queries using the UNION operator

  • Manipulate strings, dates, & numeric data using functions to integrate data from different sources into fields with the correct format for analysis

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More about this course

SQL for Data Science teaches SQL fundamentals and techniques essential for extracting, manipulating, and analyzing data in relational databases

Learners gain skills in querying, joining tables, filtering data, and using functions to derive insights, making it an indispensable tool for data analysis and decision-making in various industries

SQL for Data Science
 at 
Coursera 
Curriculum

Getting Started and Selecting & Retrieving Data with SQL
Filtering, Sorting, and Calculating Data with SQL
Subqueries and Joins in SQL
Modifying and Analyzing data with SQL

Faculty Icon

SQL for Data Science
 at 
Coursera 
Faculty details

Sadie St. Lawrence
Sadie St. Lawrence is is the Founder and CEO of Women in Data, a national non-profit organization focused on increasing diversity, creating connections, and driving meaning from data.

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SQL for Data Science
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