Data Analysis & Business Intelligence with MySQL/Python/SQL

Data Analysis & Business Intelligence with MySQL/Python/SQL, available at $19.99, has an average rating of 4.75, with 63 lectures, based on 2 reviews, and has 34 subscribers.

You will learn about Write SQL queries to explore and analyse databases with MySQL Workbench Learn how to use SQL to extract, sort, filter, and group data quickly and efficiently Analyse data across multiple tables with MySQL JOIN statements Analyse data and perform calculations using aggregate function Analyse data using subqueries Analyse data using various functions Analyse data using various Operators Analyse and manipulate data using Python & Pandas Perform data cleaning with Python Visualize data with Python This course is ideal for individuals who are Data Analysts or Business Intelligence Analyst or Data Scientist It is particularly useful for Data Analysts or Business Intelligence Analyst or Data Scientist.

Enroll now: Data Analysis & Business Intelligence with MySQL/Python/SQL

Summary

Title: Data Analysis & Business Intelligence with MySQL/Python/SQL

Price: $19.99

Average Rating: 4.75

Number of Lectures: 63

Number of Published Lectures: 63

Number of Curriculum Items: 63

Number of Published Curriculum Objects: 63

Original Price: $44.99

Quality Status: approved

Status: Live

What You Will Learn

Write SQL queries to explore and analyse databases with MySQL Workbench
Learn how to use SQL to extract, sort, filter, and group data quickly and efficiently
Analyse data across multiple tables with MySQL JOIN statements
Analyse data and perform calculations using aggregate function
Analyse data using subqueries
Analyse data using various functions
Analyse data using various Operators
Analyse and manipulate data using Python & Pandas
Perform data cleaning with Python
Visualize data with Python

Who Should Attend

Data Analysts
Business Intelligence Analyst
Data Scientist

Target Audiences

Data Analysts
Business Intelligence Analyst
Data Scientist

SQL stands for Structured Query Language. SQL lets you access and manipulate databases.

SQL can execute queries against a database. SQL can retrieve data from a database.

Most of the SQL database programs also have their own proprietary extensions in addition to the SQL standard!

MySQL is an open-source relational database management system. MySQL is currently owned by Oracle and MySQL is free and open-sourced under the terms of the GNU General Public License and available under a variety of proprietary licenses.

MySQL is used by many database-driven web applications such as Drupal, Joomla, and WordPress.

You will learn how to write queries in SQL (specifically MySQL) that will allow us to access the data inside a database.

What is Python? Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis.

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool,

built on top of the Python programming language.

In this course we will query, analyse and retrieve data from a MySQL Database using SQL and also analyse and manipulate pandas data frame with Python and also visualize data. We will also be performing some data cleaning using Python.

Course Curriculum

Chapter 1: MySQL Setup

Lecture 1: Introduction

Lecture 2: What is Data Analysis

Lecture 3: What is business intelligence

Lecture 4: What is SQL

Lecture 5: What is MySQL

Lecture 6: MySQL Installation on Macs

Lecture 7: MySQL Installation on Windows

Lecture 8: Connecting to MySQL Server

Lecture 9: What is MySQL Workbench

Lecture 10: Installing MySQL Workbench on Macs

Lecture 11: Basic Database Concepts

Lecture 12: What is a Schema

Lecture 13: MySQL Data Types

Lecture 14: Displaying MySQL Databases in MySQL Workbench

Lecture 15: View MySQL Database Tables using MySQL Workbench

Lecture 16: Overview of Data Analysis & Business Intelligence with MySQL/Python/SQL

Chapter 2: Querying Data

Lecture 1: Query a single Table

Lecture 2: Using WHERE Clause in your query

Lecture 3: Using ORDER BY Clause in your query

Lecture 4: Using GROUP BY Clause in your query

Lecture 5: Using HAVING Clause in your query

Lecture 6: Excluding duplicates in query results

Lecture 7: Limiting data returned by a query

Lecture 8: Query data with the Character Length Function

Lecture 9: Query data with the CONCAT Function

Lecture 10: Query data using a Subquery

Lecture 11: Query data using a Nested Subquery

Lecture 12: Query data using a Derived Table

Lecture 13: Query data using BETWEEN Operator

Lecture 14: Query data using IN Operator

Lecture 15: Query data using LIKE Operator

Lecture 16: Query data using UNION Operator

Chapter 3: Analysing Multiple Tables with Joins

Lecture 1: What are Table Joins

Lecture 2: Analysing data with INNER JOIN

Lecture 3: Analysing data with LEFT JOIN

Lecture 4: Analysing data with RIGHT JOIN

Lecture 5: Analysing data with SELF JOIN

Chapter 4: Analysing Data with Aggregate Functions

Lecture 1: What are Aggregate Functions

Lecture 2: Query data using AVG Aggregate Function

Lecture 3: Query data using COUNT Aggregate Function

Lecture 4: Query data using SUM Aggregate Function

Lecture 5: Query data using MIN Aggregate Function

Lecture 6: Query data using MAX Aggregate Function

Chapter 5: Python and Jupyter Notebook Setup

Lecture 1: What is Python

Lecture 2: What is Jupyter NoteBook

Lecture 3: Installing Jupyter Notebook Server

Lecture 4: Running Jupyter Notebook Server

Lecture 5: Some Jupyter Notebook Commands

Lecture 6: Jupyter Notebook components

Lecture 7: Jupyter Notebook Dashboard

Lecture 8: Jupyter Notebook Interface

Lecture 9: Create a Jupyter Notebook

Chapter 6: Data Analysis using Python

Lecture 1: Kaggle Datasets

Lecture 2: Tabular Data

Lecture 3: Exploring Pandas DataFrame

Lecture 4: Analysing and manipulating Pandas DataFrame

Lecture 5: What is Data Cleaning

Lecture 6: Performing Data Cleaning

Lecture 7: Data Visualization

Lecture 8: Visualizing qualitative data

Lecture 9: Visualizing quantitative data

Chapter 7: Hands -on Practice Questions

Lecture 1: Hands on Practice Questions

Lecture 2: Step by Step Examples

Instructors

Digital Learning Academy
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