SQL for Data Science

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

Instructor: Sadie St. Lawrence

Access provided by Toshiba Software India

711,127 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

17,151 reviews

Beginner level

No prior experience required

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

90%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

17,151 reviews

Beginner level

No prior experience required

Flexible schedule

2 weeks at 10 hours a week

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

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments¹

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Taught in English

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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.

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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 videos Total 51 minutes

Course Introduction 4 minutes
What is SQL Anyway? 7 minutes
Data Models, Part 1: Thinking About Your Data 6 minutes
Data Models, Part 2: The Evolution of Data Models 4 minutes
Data Models, Part 3: Relational vs. Transactional Models 6 minutes
Retrieving Data with a SELECT Statement 5 minutes
Creating Tables 8 minutes
Creating Temporary Tables 4 minutes
Adding Comments to SQL 5 minutes
Summary 2 minutes

3 readings Total 65 minutes

Course Navigation and Online Safety Statement 15 minutes
SQL Overview 15 minutes
Data Modeling and ER Diagrams 35 minutes

5 assignments Total 120 minutes

Introduction to SQL for Data Science 20 minutes
Let's Practice! 30 minutes
Practice Simple Select Queries 30 minutes
Module 1 Quiz 30 minutes
Module 1 Coding Questions 10 minutes

1 discussion prompt Total 30 minutes

Comparing NoSQL and SQL 30 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 videos Total 49 minutes

Module Introduction 2 minutes
Basics of Filtering with SQL 9 minutes
Advanced Filtering: IN, OR, and NOT 7 minutes
Using Wildcards in SQL 7 minutes
Sorting with ORDER BY 5 minutes
Math Operations 4 minutes
Aggregate Functions 7 minutes
Grouping Data with SQL 6 minutes
Putting it All Together 3 minutes

1 reading Total 25 minutes

SQL for Various Data Science Languages 25 minutes

3 assignments Total 105 minutes

Module 2 Practice Quiz 30 minutes
Module 2 Quiz 30 minutes
Module 2 Coding Assignment 45 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 videos Total 58 minutes

Module Introduction 1 minute
Using Subqueries 7 minutes
Subquery Best Practices and Considerations 8 minutes
Joining Tables: An Introduction 5 minutes
Cartesian (Cross) Joins 4 minutes
Inner Joins 8 minutes
Aliases and Self Joins 6 minutes
Advanced Joins: Left, Right, and Full Outer Joins 8 minutes
Unions 5 minutes
Summary 6 minutes

2 readings Total 20 minutes

SQL and Python 10 minutes
Union and Union All 10 minutes

3 assignments Total 105 minutes

Practice Quiz - Writing Queries 30 minutes
Module 3 Quiz 30 minutes
Module 3 Coding Assignment 45 minutes

1 discussion prompt Total 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 videos Total 56 minutes

Module Introduction 1 minute
Working with Text Strings 7 minutes
Working with Date and Time Strings 5 minutes
Date and Time Strings Examples 5 minutes
Case Statements 7 minutes
Views 7 minutes
Data Governance and Profiling 6 minutes
Using SQL for Data Science, Part 1 6 minutes
Using SQL for Data Science, Part 2 6 minutes
USDA Acknowledgment Video 2 minutes
Course Summary 2 minutes

3 readings Total 61 minutes

Additional SQL Resources to Explore 15 minutes
Final Project Instructions, Scripts, & Datasets 45 minutes
USDA Acknowledgment 1 minute

4 assignments Total 155 minutes

Practice Final Project 45 minutes
Module 4 Quiz 30 minutes
Module 4 Coding Questions 35 minutes
Final Project 45 minutes

1 discussion prompt Total 15 minutes

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

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Instructor

Instructor ratings

(4,833 ratings)

Sadie St. Lawrence

University of California, Davis

4 Courses 730,461 learners

Offered by

University of California, Davis

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Showing 3 of 17151

Reviewed on 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.

Reviewed on Jul 19, 2020

Please Included examples while the instructor is teaching in the video lectures. The instructor is very talented in teaching but due to lack of examples in the video it downgrades the overall course.

Reviewed on Nov 10, 2019

Videos are a bit lengthy course could be shorter by 10-20% from a time perspective with the content staying the same. Overall good course for anyone that need to learn or to refresh their skills.

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