Overview:
Welcome to "Learn MySQL from Scratch for Data Science and Analytics"! This course serves as your comprehensive guide to mastering MySQL, the popular relational database management system, for data science and analytics. MySQL is a fundamental tool for storing, managing, and analyzing data, making it essential for anyone pursuing a career in data science or analytics. In this course, you'll dive deep into MySQL, learning how to design databases, write SQL queries, and manipulate data to extract valuable insights.- Interactive video lectures by industry experts
- Instant e-certificate
- Fully online, interactive course with Professional voice-over
- Developed by qualified first aid professionals
- Self paced learning and laptop, tablet, smartphone friendly
- 24/7 Learning Assistance
- Discounts on bulk purchases
Main Course Features:
- Thorough coverage of MySQL fundamentals, including database design and normalization
- Hands-on projects and exercises to reinforce learning
- Writing complex SQL queries to retrieve and manipulate data
- Implementation of joins, subqueries, and aggregate functions for data analysis
- Guidance on indexing, optimization, and performance tuning in MySQL
- Best practices for data modeling and schema design for analytics
- Real-world case studies and examples to illustrate MySQL applications in data science
- Access to a supportive online community for collaboration and assistance
Who Should Take This Course:
- Aspiring data scientists and analysts seeking to master MySQL for data manipulation and analysis
- Database administrators looking to enhance their SQL skills for data science applications
- Students and professionals aiming to build a strong foundation in relational databases for analytics
Learning Outcomes:
- Master MySQL fundamentals, including database design, SQL queries, and data manipulation
- Perform complex data analysis tasks using SQL, including joins, subqueries, and aggregations
- Design efficient database schemas and optimize query performance in MySQL
- Apply MySQL skills to real-world data science and analytics projects
- Extract valuable insights from large datasets using MySQL for data manipulation
- Debug and troubleshoot SQL queries effectively in MySQL
- Build a portfolio of MySQL projects showcasing data science and analytics skills
- Stay updated with the latest trends and techniques in MySQL for data science and analytics.
Certification
Once you’ve successfully completed your course, you will immediately be sent a digital certificate. All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.Assessment
At the end of the Course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.Course Content
88 Lectures 5hr 47min
Learn MySQL Server from Scratch for Data Science and Analytics - 0 lessons
No lessons available.
Section 01: Getting Started - 6 lessons
Introduction
How to get course requirements
Getting started on Windows, Linux or Mac
How to ask great questions
FAQ’s
What is Source Code?
Section 02: SQL Server setting up - 5 lessons
Section Introduction
MySQL Server Installation
Connect MySQL Server Instance
MySQL Workbench overview
Download and Restore Sample Database
Section 03: SQL Database basics - 11 lessons
Section Introduction
Overview of Databases
Creating Database
SQL Data Types
Column Data Types on Workbench
Creating Table
Overview of Primary and Foreign Key
Primary Key
Foreign Key
Creating Temporary tables
EER – Enhanced Entity Relationship Diagrams
Section 04: SQL DML (Data Manipulation Language) - 4 lessons
Section Introduction
Insert statement
Update statement
Delete statement
Section 05: SQL DDL (Data Definition Language) - 7 lessons
Section Introduction
CREATE table statement
DROP statement
ALTER statement
TRUNCATE statement
COMMENT in query
RENAME table
Section 06: SQL DCL (Data Control Language) - 3 lessons
Create Database user
GRANT permissions
REVOKE permissions
Section 07: SQL Statement Basic - 7 lessons
Section Introduction
SQL Statement basic
SELECT Statement
SELECT DISTINCT
SELECT with column headings
Column AS statement
DASHBOARD Analytics
Section 08: Filtering Data rows - 2 lessons
SELECT WHERE Clause – theory
SELECT WHERE Clause – practical
Section 09: Aggregate functions for Data Analysis - 2 lessons
Sum()
Min()-Max()
Section 10: SQL Data Analyticstatements - 5 lessons
Order By statement
SELECT TOP 3 records
BETWEEN command
IN operator
Search Data usingLIKE cards
Section 11: SQL Group by statement - 4 lessons
Section Introduction
Group by – theory
Data Analytics with Group By
HAVING statement
Section 12: JOINS - 9 lessons
Overview of Joins
What are Joins
Inner join
Left outer join
Right outer join
Union
CERTESIAN Product or Cross Join
Query Exercise
Solution for Query Exercise
Section 13: SQL Constraints - 4 lessons
Section introduction
Check constraint
NOT NULL constraint
UNIQUE constraint
Section 14: Views - 2 lessons
Creating Views
Data Analytic Views from multiple tables
Section 15: Advanced SQL Functions - 8 lessons
Section Introduction
Timestamp
Extract from timestamp
Mathematical scalar functions
String functions
Advanced functions
Sub Queries
SELECT with calculations
Section 16: SQL Stored procedures - 3 lessons
Create stored procedure
Stored procedure with parameter
Drop Procedure
Section 17: Import & Export data - 3 lessons
Section Introduction
Import .csv file
Export Data to .csv file
Section 18: Backup and Restore Database - 3 lessons
Section Introduction
Creating Database backup
Restoring Database backup