MySQL Bootcamp - The Complete 2026 Introduction!

Explore databases as organized data collections and how MySQL uses a database management system to store information in tables like customers, orders, returns, and inventory, and SQL vs MySQL.

Understand how SQL, a structured query language for relational databases, differs from MySQL, a free and open database management system that coordinates SQL commands to fetch and manage data.

Install MySQL Workbench and the MySQL community server on macOS. Download the two components from dev.mysql.com, configure a local server, and use the MySQL Workbench graphical user interface to manage it.

Use MySQL Workbench to run a local server, import the DVD rental schema and its data, then explore tables and columns to practice fetching and joining queries.

Learn how to use the select keyword to fetch specific columns from a table, avoid select star, and practice with customers, orders, and the actor table.

Learn to fetch a single column like last_update from the actor table, practice selecting multiple columns from language and address tables, and understand SQL's case-insensitive keywords and readability conventions.

Solve the first challenge by selecting the rating and rental_rate columns from the film table in MySQL Workbench, reinforcing practical SQL querying skills.

See how the order by keyword sorts select results by one or more columns, using asc for ascending and dsc for descending, as in sorting by id and customer name.

Sort data with the order by keyword in MySQL, ordering by first_name, last_name, or customer_id in ascending or descending order. Explore sorting by title in the film table.

Learn to sort data with order by across multiple columns. Sort first by customer name in ascending order and then by age in descending order, with actor and film examples in MySQL workbench.

Practice sorting results with order by, sorting customers by first name descending and by last name then first name ascending, and films by release year ascending and rental rate descending.

Practice solving order by queries in SQL, sorting customer and film data by first name desc, last name asc, and release year asc with rental rate desc.

Explore how the limit keyword restricts query results to the top n rows, improving performance by avoiding extra data; see an example ordering by name and age, then three rows.

Master practical uses of the limit keyword in sql by combining order by and limit to fetch top rows from actor and customer tables, improving performance.

Practice limit keyword by listing rental rates for top five most expensive films, first ten titles with release years, and first 20 customers sorted by last name then first name.

List the top five films by rental rate from the film table, and fetch the first ten titles with release year ascending.

Use select distinct to remove duplicate rows and return only unique values. Explore distinct across id, name, and combinations such as district with city_id to see duplicates.

Use the distinct keyword to return unique values from the rating column in the film table, practicing a query in MySQL Workbench.

Master the count aggregate function in SQL by comparing count star, count column, and count distinct, understanding how null values affect row counts across tables.

Count the total rows in the customer table and compute the number of distinct first names to reveal eight duplicates.

Learn how to use the as keyword to assign aliases to columns in SQL, print renamed columns like first_name, and understand that aliases only affect output, not the table.

Use the as keyword in MySQL select queries to rename columns, selecting film_id, title as movie name, and description as story from the film_text table.

Explore how to filter data with the where keyword, combine conditions with and or, and use operators like greater than, less than, and equal to in MySQL queries.

Explore using the where clause with the or operator to filter address table rows by district, selecting Alberta or Texas, and count the matching rows with count(*).

Filter the payment table with the where keyword to select rows where the amount equals 6.99 (float), then count them with count(*), illustrating approximately 1,119 matches.

apply the where keyword to filter the payment table for amounts greater than or equal to 2.99 and less than 6.99, print all columns, and count the matching rows.

Explain that null values mean missing or unknown data, distinct from empty strings or zero, and show testing with is null and is not null in queries.

Apply is null and is not null in MySQL to distinguish null values from empty strings, test postal code and phone fields, and identify empty strings in the address table.