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.
We guarantee that all our online courses will meet or exceed your
expectations. If you are not fully satisfied with a course - for
any reason at all - simply request a full refund. We guarantee no
hassles. That's our promise to you.
Go ahead and order with confidence!
Easy to Access
Let's Navigate Together
Course Curriculum
| Learn MySQL Server from Scratch for Data Science and Analytics | |||
| No lessons available in this section. | |||
| Section 01: Getting Started | |||
| 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 | |||
| Section Introduction | |||
| MySQL Server Installation | |||
| Connect MySQL Server Instance | |||
| MySQL Workbench overview | |||
| Download and Restore Sample Database | |||
| Section 03: SQL Database basics | |||
| 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) | |||
| Section Introduction | |||
| Insert statement | |||
| Update statement | |||
| Delete statement | |||
| Section 05: SQL DDL (Data Definition Language) | |||
| Section Introduction | |||
| CREATE table statement | |||
| DROP statement | |||
| ALTER statement | |||
| TRUNCATE statement | |||
| COMMENT in query | |||
| RENAME table | |||
| Section 06: SQL DCL (Data Control Language) | |||
| Create Database user | |||
| GRANT permissions | |||
| REVOKE permissions | |||
| Section 07: SQL Statement Basic | |||
| Section Introduction | |||
| SQL Statement basic | |||
| SELECT Statement | |||
| SELECT DISTINCT | |||
| SELECT with column headings | |||
| Column AS statement | |||
| DASHBOARD Analytics | |||
| Section 08: Filtering Data rows | |||
| SELECT WHERE Clause – theory | |||
| SELECT WHERE Clause – practical | |||
| Section 09: Aggregate functions for Data Analysis | |||
| Sum() | |||
| Min()-Max() | |||
| Section 10: SQL Data Analyticstatements | |||
| Order By statement | |||
| SELECT TOP 3 records | |||
| BETWEEN command | |||
| IN operator | |||
| Search Data usingLIKE cards | |||
| Section 11: SQL Group by statement | |||
| Section Introduction | |||
| Group by – theory | |||
| Data Analytics with Group By | |||
| HAVING statement | |||
| Section 12: JOINS | |||
| 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 | |||
| Section introduction | |||
| Check constraint | |||
| NOT NULL constraint | |||
| UNIQUE constraint | |||
| Section 14: Views | |||
| Creating Views | |||
| Data Analytic Views from multiple tables | |||
| Section 15: Advanced SQL Functions | |||
| Section Introduction | |||
| Timestamp | |||
| Extract from timestamp | |||
| Mathematical scalar functions | |||
| String functions | |||
| Advanced functions | |||
| Sub Queries | |||
| SELECT with calculations | |||
| Section 16: SQL Stored procedures | |||
| Create stored procedure | |||
| Stored procedure with parameter | |||
| Drop Procedure | |||
| Section 17: Import & Export data | |||
| Section Introduction | |||
| Import .csv file | |||
| Export Data to .csv file | |||
| Section 18: Backup and Restore Database | |||
| Section Introduction | |||
| Creating Database backup | |||
| Restoring Database backup | |||