MySQL for Data Analytics

Course details

This course has practical, guided projects that provide hands-on experience in applying SQL concepts to real-world scenarios. From data cleaning to exploratory data analysis, you'll gain the proficiency to tackle data challenges head-on and extract valuable insights from diverse datasets. You’ll also learn how professionals use and work within MySQL. Learn about staging databases, production databases, naming conventions, and more so you can expand your SQL expertise and excel in data analysis.

Learning objectives
Analyze, clean, and explore data in MySQL.
Use Window functions for data analysis.
Use regular expression for data analysis.
Build portfolio projects of data analytics.

Concepts

Introduction

Instructor introduction
Course introduction

Getting Started in MySQL

What is SQL
How is SQL used
Download and install MySQL (Microsoft users)I
Creating databases
MySQL UI walkthrough

Querying Basics

Querying introduction
Basics of querying
Select statement
Where clause
Comparison operators
Logical operators
IN operator
Between
Like operator
Order by clause
Limit
Aliasing

Data Types and Functions

Data types introduction
Numeric data types
String functions
Date and date format functions
IF functions
Case statements
Cast and convert functions

Group By

Group by introduction
Group by basics
Aggregate functions
Having vs where clause
Rollup

Joins

Joins introduction
Inner joins
Joining multiple tables
Joining on multiple conditions
Outer joins
Self joins
Cross joins
Natural join
USING keyword
Unions
Join use cases

Subqueries

Subquery introduction
Subquery basics
ANY and ALL operators
Exists
Subqueries in select and from

Window Functions

Window functions introduction
Window functions basics - Over + partition by
Row number
Rank and dense rank
Lag and lead

Regular Expression

Regular expression introduction
Regular expression methods
Regular expression metacharacters
Regular expression examples and use cases

Working with Files

Importing data into MySQL
Export data to CSV

Data Cleaning

Data cleaning introduction
Removing duplicates
Standardize data
Breaking one column into multiple columns
Working with null values
Deleting columns

Full Projects

Projects introduction
World life expectancy data cleaning
World life expectancy exploratory data analysis
US household income data cleaning
US household income exploratory data analysis