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

11,569 ratings
2,982 reviews

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

Aug 22, 2021

I thought this course was great! Great introduction to Relational Databases and SQLite. Highly reccomend for anyone new to SQL, Databases, or someone looking to get started with a data science career.

Apr 5, 2020

This course has really helped with optimizing queries that I work with everyday, enhancing my understanding of RDBMS, joins, analyzing and structuring exactly what you need and yielding those results.

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2901 - 2925 of 3,041 Reviews for SQL for Data Science

By Priyanshu V

Jul 31, 2020

Some topic is not cover like constraints alter modify default

By Tim S

Jul 8, 2020

Quite easy. The peer-reviewed assignment is also very easy.

By liqi x

Dec 24, 2019

not enough teaching examples, could be tough for beginner

By Ashish D

Jun 29, 2021

Explanations could be improved with the help of examples


Jun 25, 2020

Very fast and high level for a person who knows nothing

By Saulo G d M S

Jul 27, 2020

A really good course, but the forum isn't that great.

By Karan D K

Oct 19, 2021

I​mportant topics like window functions are missing.


Feb 24, 2021

Could be more better. You could have taught more SQL

By Phillipe S S R

Jan 3, 2018

Quiz and graded materials not available for free.

By Hari G

Dec 11, 2019

Too much theory and very little or no practice

By Deleted A

Jul 5, 2021

The course is basically theoretical.

By dager6

May 4, 2018

Good general basic introductions.

By Tong Z

Dec 26, 2021

do not like the peer review part

By Gaoge Z

Jan 4, 2021

Could show results in demos.

By Fabian M

Mar 16, 2021

Too little practice

By Renuka G

Dec 20, 2019

good one

By 318126512050 S R B

Jun 21, 2021


By Carl D A

Aug 13, 2020


By Krishna G

Jun 10, 2020


By Chen G

Feb 15, 2019


By Gergely H

Jul 30, 2021


By renas c

Mar 12, 2021


By Manas d

Sep 19, 2020


By Ben T

Dec 12, 2021

Really bad. I'm trying to be fair here, and I understand that there are reasons the instructors made some choices that they did, however:

-You can't teach a course designed for absolute beginners and not help us install a chosen software and explain the interface. I felt SO LOST trying to download SQLite on my own, and then find out the instructor chose to teach a software with NO USER INTERFACE from the download. Why would anyone chose SQLite as the software FOR A COMPLETE BEGINNER: I have no idea. I ended up using a different course (see below) and used MySQL as my software (free, great user interface, not so intimidating for a beginner.

-I can't stress this enough: THIS IS A THEORETICAL COURSE. There is no videos in which the instructor has an SQL software open and you code along with them. IF THAT'S WHAT YOU WANT go to "Programming with Mosh." The way that this course works is, she just talks about SQL: you never are given a database from which to query / retrieve / test your programming. Like, how is this even a course if you're not at least providing some sample data to work with?

I'm really disappointed in Coursera: I've completed two specializations here already, really enjoyed each and had no desire to leave the website, but after this I'm going to be much more careful and looking at other websites like Udemy.

By Eric R

May 21, 2021

Weeks 1 - 3 contained good information and had good problem sets. Week 4 totally drops the ball. The lectures do not fully flesh out the many uses of datetimes, cases or views. The problem sets for week 4 should be much more extensive to practice these concepts. The lectures on sql for Data Science are fluff - no skills are included; and then the student is expected to perform these skills in the peer reviewed assignment. The peer review assignment has several poorly specified questions. Overall the lectures could be improved by showing the ER diagrams for the tables the lecturer is referring to rather than only showing a query. Many lectures should be reshot where the lecturer misspeaks/does not complete her thought, or where she burps while speaking.