Learn MySQL from Scratch for Data Science and Analytics

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Learn MySQL from Scratch for Data Science and Analytics

Learn MySQL from Scratch for Data Science and Analytics

Level: Intermediate
Modules: 88 Modules
Duration: 5 hours, 47 minutes
Students: 9

Embark on a comprehensive journey into the world of MySQL with a focus on its applications in Data Science and Analytics. This course is structured to take you from the fundamentals to advanced topics in MySQL Server. Covering SQL basics, data manipulation and definition, control and analytic functions, and database management, you’ll acquire the essential skills for harnessing MySQL’s power in data-driven decision-making.

Learning Outcomes:

Establish a strong foundation in SQL and MySQL.
Set up and configure SQL Server for efficient data handling.
Master SQL’s Data Manipulation, Definition, and Control Language.
Create and optimize SQL queries for data analysis.
Perform advanced data analytics using SQL.
Understand the power of GROUP BY and JOIN statements.
Implement data constraints and views for data integrity and security.
Develop proficiency in stored procedures, data import/export, and database backup/restore.

Why buy this Learn MySQL from Scratch for Data Science and Analytics?

Unlimited access to the course for forever
Digital Certificate, Transcript, student ID all included in the price
Absolutely no hidden fees
Directly receive CPD accredited qualifications after course completion
Receive one to one assistance on every weekday from professionals
Immediately receive the PDF certificate after passing
Receive the original copies of your certificate and transcript on the next working day
Easily learn the skills and knowledge from the comfort of your home

Certification

After studying the course materials of the Learn MySQL from Scratch for Data Science and Analytics you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.

Who is this course for?

This Learn MySQL from Scratch for Data Science and Analytics course is ideal for

Aspiring Data Scientists and Analysts.
Database Administrators and Developers.
Students and professionals seeking to enter the field of Data Science.
Anyone looking to enhance their SQL and MySQL skills for data-related roles.

Prerequisites

This Learn MySQL from Scratch for Data Science and Analytics was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.

Career path

Data Analyst: £25,000 – £50,000 per year.
Database Administrator: £30,000 – £60,000 per year.
SQL Developer: £30,000 – £60,000 per year.
Data Scientist: £40,000 – £80,000 per year.
Business Intelligence Analyst: £35,000 – £65,000 per year.

Course Curriculum

Learn MySQL from Scratch for Data Science and Analytics
Section 01: Getting Started
	Introduction	00:02:00
	How to get course requirements	00:01:00
	Getting started on Windows, Linux or Mac	00:01:00
	How to ask great questions	00:01:00
	FAQ’s	00:01:00
	What is Source Code?	00:09:00
Section 02: SQL Server setting up
	Section Introduction	00:01:00
	MySQL Server Installation	00:14:00
	Connect MySQL Server Instance	00:06:00
	MySQL Workbench overview	00:11:00
	Download and Restore Sample Database	00:08:00
Section 03: SQL Database basics
	Section Introduction	00:01:00
	Overview of Databases	00:09:00
	Creating Database	00:07:00
	SQL Data Types	00:04:00
	Column Data Types on Workbench	00:07:00
	Creating Table	00:04:00
	Overview of Primary and Foreign Key	00:03:00
	Primary Key	00:06:00
	Foreign Key	00:12:00
	Creating Temporary tables	00:12:00
	EER – Enhanced Entity Relationship Diagrams	00:04:00
Section 04: SQL DML (Data Manipulation Language)
	Section Introduction	00:01:00
	Insert statement	00:07:00
	Update statement	00:06:00
	Delete statement	00:03:00
Section 05: SQL DDL (Data Definition Language)
	Section Introduction	00:01:00
	CREATE table statement	00:08:00
	DROP statement	00:03:00
	ALTER statement	00:05:00
	TRUNCATE statement	00:03:00
	COMMENT in query	00:02:00
	RENAME table	00:03:00
Section 06: SQL DCL (Data Control Language)
	Create Database user	00:03:00
	GRANT permissions	00:06:00
	REVOKE permissions	00:04:00
Section 07: SQL Statement Basic
	Section Introduction	00:01:00
	SQL Statement basic	00:03:00
	SELECT Statement	00:03:00
	SELECT DISTINCT	00:02:00
	SELECT with column headings	00:01:00
	Column AS statement	00:02:00
	DASHBOARD Analytics	00:06:00
Section 08: Filtering Data rows
	SELECT WHERE Clause – theory	00:03:00
	SELECT WHERE Clause – practical	00:06:00
Section 09: Aggregate functions for Data Analysis
	Sum()	00:06:00
	Min()-Max()	00:03:00
Section 10: SQL Data Analyticstatements
	Order By statement	00:05:00
	SELECT TOP 3 records	00:02:00
	BETWEEN command	00:06:00
	IN operator	00:03:00
	Search Data usingLIKE cards	00:05:00
Section 11: SQL Group by statement
	Section Introduction	00:01:00
	Group by – theory	00:04:00
	Data Analytics with Group By	00:04:00
	HAVING statement	00:03:00
Section 12: JOINS
	Overview of Joins	00:02:00
	What are Joins	00:02:00
	Inner join	00:07:00
	Left outer join	00:02:00
	Right outer join	00:02:00
	Union	00:03:00
	CERTESIAN Product or Cross Join	00:03:00
	Query Exercise	00:01:00
	Solution for Query Exercise	00:01:00
Section 13: SQL Constraints
	Section introduction	00:01:00
	Check constraint	00:09:00
	NOT NULL constraint	00:03:00
	UNIQUE constraint	00:06:00
Section 14: Views
	Creating Views	00:03:00
	Data Analytic Views from multiple tables	00:03:00
Section 15: Advanced SQL Functions
	Section Introduction	00:01:00
	Timestamp	00:03:00
	Extract from timestamp	00:03:00
	Mathematical scalar functions	00:03:00
	String functions3	00:07:00
	Advanced functions	00:04:00
	Sub Queries	00:03:00
	SELECT with calculations	00:05:00
Section 16: SQL Stored procedures
	Create stored procedure	00:06:00
	Stored procedure with parameter	00:03:00
	Drop Procedure	00:01:00
Section 17: Import & Export data
	Section Introduction	00:01:00
	Import .csv file	00:04:00
	Export Data to .csv file	00:02:00
Section 18: Backup and Restore Database
	Section Introduction	00:01:00
	Creating Database backup	00:02:00
	Restoring Database backup	00:02:00