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

4.7

stars

22,504 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

Dec 27, 2019

Course is god enough. However the last assessment is not. Misprints and not clear questions lead to disappointing marks in the end. Also other students marked assessments based on their understanding.

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!

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By Priya R

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Mar 21, 2025

GOOD

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Mar 21, 2025

good

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good

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Mar 19, 2025

GOOD

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Mar 19, 2025

Good

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Mar 19, 2025

good

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Mar 19, 2025

nice

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Mar 19, 2025

good

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Mar 19, 2025

good

By Prince R

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Mar 18, 2025

vjhk

By SIMRAN

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Mar 18, 2025

nice

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Mar 18, 2025

good

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Mar 18, 2025

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Mar 18, 2025

Good

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Mar 18, 2025

nice

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Mar 18, 2025

good

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Mar 18, 2025

Good