University of California, Davis
Taught by: Sadie St. Lawrence, Data Scientist at VSP Global Founder and Executive Director, Women in Data (WID)
About 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!
#Syllabus
#WEEK 1
Getting Started and Selecting & Retrieving Data with SQL
In this module, you will be able to define SQL and discuss how SQL differs from other computer languages. You will be able to 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 be able to use the SELECT statement and talk about some basic syntax rules. You will be able to add comments in your code and synthesize its importance.
11 videos, 2 readings, 2 practice quizzes
Discussion Prompt: Your Goals For This Course...
Video: Course Introduction
Video: Module Introduction
Video: What is SQL Anyway?
Video: Data Models, Part 1: Thinking About Your Data
Video: Data Models, Part 2: The Evolution of Data Models
Video: Data Models, Part 3: Relational vs. Transactional Models
Video: Retrieving Data with a SELECT Statement
Video: Creating Tables
Video: Creating Temporary Tables
Video: Adding Comments to SQL
Practice Quiz: Let's Practice!
Practice Quiz: Practice Simple Select Queries
Video: Summary
Reading: SQL Overview
Reading: Data Modeling and ER Diagrams
Discussion Prompt: Comparing NoSQL and SQL
Graded: Module 1 Quiz
Graded: Module 1 Coding Questions
#WEEK 2
Filtering, Sorting, and Calculating Data with SQL
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.
9 videos, 1 reading
Video: Module Introduction
Video: Basics of Filtering with SQL
Video: Advanced Filtering: IN, OR, and NOT
Video: Using Wildcards in SQL
Video: Sorting with ORDER BY
Video: Math Operations
Video: Aggregate Functions
Video: Grouping Data with SQL
Video: Putting it All Together
Reading: SQL for Various Data Science Languages
Graded: Module 2 Quiz
Graded: Module 2 Coding Assignment
#WEEK 3
Subqueries and Joins in SQL
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.
10 videos, 2 readings
Video: Module Introduction
Video: Using Subqueries
Video: Subquery Best Practices and Considerations
Video: Joining Tables: An Introduction
Video: Cartesian (Cross) Joins
Video: Inner Joins
Video: Aliases and Self Joins
Video: Advanced Joins: Left, Right, and Full Outer Joins
Video: Unions
Video: Summary
Reading: SQL and Python
Reading: Union and Union All
Discussion Prompt: What do you think you'll use?
Graded: Module 3 Quiz
Graded: Module 3 Coding Assignment
#WEEK 4
Modifying and Analyzing Data with SQL
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.
10 videos, 3 readings
Video: Module Introduction
Video: Working with Text Strings
Video: Working with Date and Time Strings
Video: Date and Time Strings Examples
Video: Case Statements
Video: Views
Video: Data Governance and Profiling
Video: Using SQL for Data Science, Part 1
Video: Using SQL for Data Science, Part 2
Reading: Additional SQL Resources to Explore
Reading: Welcome to Peer Review Assignments!
Reading: Yelp Dataset SQL Lookup
Video: Course Summary
Discussion Prompt: How do you plan on using SQL in the future?
Graded: Module 4 Quiz
Graded: Module 4 Coding Questions
Graded: Data Scientist Role Play: Profiling and Analyzing the Yelp Dataset