SQL for Data Science

This course is part of Learn SQL Basics for Data Science Specialization

Instructor: Sadie St. Lawrence

721,979 already enrolled

Included with

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

No prior experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

90%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

No prior experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

90%

Most learners liked this course

What you'll learn

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.

Skills you'll gain

Category: Data Science
Category: Data Governance
Category: Data Wrangling
Category: Data Transformation
Category: SQL
Category: Data Manipulation
Category: Data Modeling
Category: Database Management
Category: Data Quality
Category: Descriptive Analytics
Category: Data Literacy
Category: Data Analysis

Tools you'll learn

Category: Query Languages
Category: Relational Databases

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments¹

AI Graded see disclaimer

Taught in English

Build your subject-matter expertise

This course is part of the Learn SQL Basics for Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this 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!

In this module, you will be able to define SQL and discuss how SQL differs from other computer languages. Additionally, compare and contrast the roles of a database administrator and a data scientist, and explain the differences between one-to-one, one-to-many, and many-to-many relationships with databases. You will also be able to use the SELECT statement and talk about some basic syntax rules, add comments in your code, and synthesize their importance.

What's included

10 videos3 readings5 assignments1 discussion prompt

10 videosTotal 51 minutes

Course Introduction4 minutes
What is SQL Anyway?7 minutes
Data Models, Part 1: Thinking About Your Data6 minutes
Data Models, Part 2: The Evolution of Data Models4 minutes
Data Models, Part 3: Relational vs. Transactional Models6 minutes
Retrieving Data with a SELECT Statement5 minutes
Creating Tables8 minutes
Creating Temporary Tables4 minutes
Adding Comments to SQL5 minutes
Summary2 minutes

3 readingsTotal 65 minutes

Course Navigation and Online Safety Statement15 minutes
SQL Overview15 minutes
Data Modeling and ER Diagrams35 minutes

5 assignmentsTotal 120 minutes

Module 1 Quiz30 minutes
Module 1 Coding Questions10 minutes
Introduction to SQL for Data Science20 minutes
Let's Practice!30 minutes
Practice Simple Select Queries30 minutes

1 discussion promptTotal 30 minutes

Comparing NoSQL and SQL30 minutes

In this module, you will be able to use several more new clauses and operators including WHERE, BETWEEN, IN, OR, NOT, LIKE, ORDER BY, and GROUP BY. You will be able to use the wildcard function to search for more specific or parts of records, including their advantages and disadvantages, and how best to use them. You will be able to discuss how to use basic math operators, as well as aggregate functions like AVERAGE, COUNT, MAX, MIN, and others to begin analyzing our data.

What's included

9 videos1 reading3 assignments

9 videosTotal 49 minutes

Module Introduction2 minutes
Basics of Filtering with SQL9 minutes
Advanced Filtering: IN, OR, and NOT7 minutes
Using Wildcards in SQL7 minutes
Sorting with ORDER BY5 minutes
Math Operations4 minutes
Aggregate Functions7 minutes
Grouping Data with SQL6 minutes
Putting it All Together3 minutes

1 readingTotal 25 minutes

SQL for Various Data Science Languages25 minutes

3 assignmentsTotal 105 minutes

Module 2 Quiz30 minutes
Module 2 Coding Assignment45 minutes
Module 2 Practice Quiz30 minutes

In this module, you will be able to discuss subqueries, including their advantages and disadvantages, and when to use them. You will be able to recall the concept of a key field and discuss how these help us link data together with JOINs. You will be able to identify and define several types of JOINs, including the Cartesian join, an inner join, left and right joins, full outer joins, and a self join. You will be able to use aliases and pre-qualifiers to make your SQL code cleaner and efficient.

What's included

10 videos2 readings3 assignments1 discussion prompt

10 videosTotal 58 minutes

Module Introduction1 minute
Using Subqueries7 minutes
Subquery Best Practices and Considerations8 minutes
Joining Tables: An Introduction5 minutes
Cartesian (Cross) Joins4 minutes
Inner Joins8 minutes
Aliases and Self Joins6 minutes
Advanced Joins: Left, Right, and Full Outer Joins8 minutes
Unions5 minutes
Summary6 minutes

2 readingsTotal 20 minutes

SQL and Python10 minutes
Union and Union All10 minutes

3 assignmentsTotal 105 minutes

Module 3 Quiz30 minutes
Module 3 Coding Assignment45 minutes
Practice Quiz - Writing Queries30 minutes

1 discussion promptTotal 20 minutes

What do you think you'll use?20 minutes

In this module, you will be able to discuss how to modify strings by concatenating, trimming, changing the case, and using the substring function. You will be able to discuss the date and time strings specifically. You will be able to use case statements and finish this module by discussing data governance and profiling. You will also be able to apply fundamental principles when using SQL for data science. You'll be able to use tips and tricks to apply SQL in a data science context.

What's included

11 videos3 readings4 assignments1 discussion prompt

11 videosTotal 56 minutes

Module Introduction1 minute
Working with Text Strings7 minutes
Working with Date and Time Strings5 minutes
Date and Time Strings Examples5 minutes
Case Statements7 minutes
Views7 minutes
Data Governance and Profiling6 minutes
Using SQL for Data Science, Part 16 minutes
Using SQL for Data Science, Part 26 minutes
USDA Acknowledgment Video2 minutes
Course Summary2 minutes

3 readingsTotal 61 minutes

Additional SQL Resources to Explore15 minutes
Final Project Instructions, Scripts, & Datasets45 minutes
USDA Acknowledgment1 minute

4 assignmentsTotal 155 minutes

Module 4 Quiz30 minutes
Module 4 Coding Questions35 minutes
Final Project45 minutes
Practice Final Project45 minutes

1 discussion promptTotal 15 minutes

How do you Plan on Using SQL in the Future?15 minutes

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Instructor

Instructor ratings

(4,841 ratings)

Sadie St. Lawrence

University of California, Davis

4 Courses742,443 learners

Offered by

University of California, Davis

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Frequently asked questions

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