Course: Querying SQL Databases: Using AI

Structured query language (SQL) is a powerful query language designed for managing and manipulating relational databases. Its declarative nature allows users to interact with databases by specifying the desired result, leaving the system to determine the optimal method of execution. Begin this course with an introduction to SQL, including the features of SQL and how and where SQL is used. Then, you will install and operate MySQL, utilizing the assistance of generative artificial intelligence (AI) chatbots ChatGPT and Bard. You will work with the MySQL Workbench and learn to create tables, insert data into tables, and update and delete records in tables. Next, you will find out how to apply constraints on tables, use NOT NULL constraints to prohibit missing values, and use unique constraints, which ensure distinct values in columns. Finally, you will create and work with primary key constraints that are used to uniquely identify records in a table.

In structured query language (SQL), filtering and grouping are fundamental operations that enable precise control and analysis of data. Begin this course by filtering your data using SQL queries. You will learn how to use the WHERE clause with comparison and logical operators to create predicates and how to use the LIKE and IN keywords for filtering. Then you will discover how to read data from a CSV file into a MySQL table using the MySQL workbench. Next, you will work with subqueries to help execute queries using data from multiple tables and you will explore foreign-key constraints to maintain referential integrity. You will examine grouping and aggregation of your data, including simple numeric aggregations like COUNT, SUM, and AVG. Finally, you will perform basic string manipulation and math operations on table columns, divide your data by categorical columns and perform aggregations for each category, and filter the results of grouped and aggregated tables.

Joins in SQL combine data from multiple tables, linking related information based on common columns. Views offer a virtual representation of data, simplifying complex queries. Triggers execute predefined actions in response to specific events and transactions safeguard against data inconsistencies in the event of failures. Begin this course by creating indexes on SQL tables to enhance query performance. Next, you will explore joining two tables in SQL, use prompt engineering to specify how you want to combine data, and have ChatGPT and Bard generate the queries you need. Then you will create and query simple views and perform normalization so that your data adheres to principles that reduce redundancy and maintain data integrity. You will create triggers for row insertions, updates, and deletes, all with generative artificial intelligence (AI) help. Finally, you will work with transactions, use prompt engineering to state your problem statement, and have generative AI write your queries for you.