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Learner Reviews & Feedback for Databases and SQL for Data Science with Python by IBM

4.7
stars
22,466 ratings

About the Course

Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts and Data Engineers. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases. In this course you will learn SQL inside out- from the very basics of Select statements to advanced concepts like JOINs. You will: -write foundational SQL statements like: SELECT, INSERT, UPDATE, and DELETE -filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses -differentiate between DML & DDL -CREATE, ALTER, DROP and load tables -use string patterns and ranges; ORDER and GROUP result sets, and built-in database functions -build sub-queries and query data from multiple tables -access databases as a data scientist using Jupyter notebooks with SQL and Python -work with advanced concepts like Stored Procedures, Views, ACID Transactions, Inner & Outer JOINs through hands-on labs and projects You will practice building SQL queries, work with real databases on the Cloud, and use real data science tools. In the final project you’ll analyze multiple real-world datasets to demonstrate your skills....

Top reviews

MM

Oct 6, 2023

This course was an Excellent, Interesting, and knowledgeful game for me. I have been excited to lean SQL and Databases and finally IBM and Coursera let my dream come true. Thanks both of them!

AZ

Feb 11, 2025

Very intriguing first exposure to SQL for CS students! Loved the integration with Python. It was a bit hard to actually learn SQL from this exclusively, so using outside resources will be helpful.

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By PAVAN K P

Oct 23, 2022

nice

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Oct 21, 2022

good

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Oct 14, 2022

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Jul 29, 2022

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Nov 22, 2021

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Mar 14, 2021

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Jan 18, 2021

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Nov 7, 2020

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Aug 11, 2020

Nice!

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Jun 14, 2020

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Jun 2, 2020

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May 24, 2020

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May 8, 2020

happy

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Mar 19, 2020

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Feb 10, 2020

lucid

By Diego B

Dec 17, 2019

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Sep 5, 2019

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May 30, 2019

great

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Mar 10, 2019

Great

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Dec 1, 2025

Best

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Oct 4, 2025

good

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Aug 11, 2025

best

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Jul 24, 2025

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Jul 6, 2025

good

By Ojas a

Jun 19, 2025

nice