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Learner Reviews & Feedback for SQL for Data Science by University of California, Davis

4.6
stars
16,990 ratings

About the Course

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems. This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables. You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results. You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!...

Top reviews

AL

Aug 21, 2020

A comprehensive course that covers major aspects of query building and retrieval in a management system. The topics were delivered well and the materials/assignments were relevant for skill-building.

KF

Apr 1, 2023

I loved the practices. I learned alot But I think some of them had mistakes... The online visual studio code never worked for me! It might be good to make a video that explains how to work with it.

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3051 - 3075 of 4,380 Reviews for SQL for Data Science

By Ángel G

Sep 6, 2020

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By vishal c k

Aug 31, 2020

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By Sowmia M

Aug 3, 2020

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By Guillem G P

Jul 29, 2025

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By shreyas l

Jul 14, 2025

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By Kiran V

Oct 18, 2023

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By DIEGO M P Q

Mar 29, 2023

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By Md S

Nov 13, 2022

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By Alperen K

Aug 18, 2022

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By Aditi D

Aug 16, 2022

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Aug 14, 2022

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By Jasper D S

Oct 4, 2021

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Jul 20, 2021

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By CHRISTIAN M T

Dec 18, 2020

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By Pierre K

Nov 30, 2020

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By Ayman M

Aug 24, 2020

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By Dwi F A

Aug 23, 2020

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By James J P

May 8, 2020

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By Omkar G

Mar 11, 2020

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By Magne V

Jul 12, 2019

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By Ganesh L

Dec 5, 2018

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By Ruohan X

Sep 2, 2025

A very helpful and valuable course with introductory lectures and practices to get into SQL. The lectures are very digestible, with small and useful quizzes throughout to consolidate the learning. The class is structured well: from basic concepts (what is SQL, what it is used for, what's the benefit of them) to writing slightly more complex queries, as long as you follow through, you'll have a good foundation for using SQL going forward. However, I do think the class may benefit from just one more 'glossary' lesson at the very beginning of the series before diving into the real content to connect the computer science/data science terminology with laymen terms. For example, as someone who works in the basic sciences that has a different definition for 'data modeling', learning what data modeling means in SQL was a surprising but useful fact. Additionally, the datasets could benefit from some context. For example, for the final project (or any project that may involve data manipulation from datasets provided), it would be great to include some data codebook so we know exactly what the data file and the column headers mean before creating new tables/importing data. This could simply be a tutorial video or a website link to the dataset that was provided. Overall very cool class to prepare me for further SQL adventures!