MySQL – Statistics for Data Science & Business Analytics

Course Curriculum

Chapter 1: Course orientation

Lecture 1: Download Course Syllabus and contents

Lecture 2: What will you get from this course ?

Lecture 3: Bookmark and Accessing course slides , codes , apps and projects

Lecture 4: How to learn and get most of the course

Lecture 5: Download Cornell notes and learn how to use it .

Lecture 6: Which part of the course matched to me ?

Chapter 2: An Introduction to SQL – MySQL – Data Science

Lecture 1: Available Jobs for data analysis or data science .

Lecture 2: Comparison between SQL , Python , and R language

Lecture 3: Understand Why MySQL for Data analysis ?

Lecture 4: Learning programming for data analysis is something easy or complex to learn it

Lecture 5: High-level overview about course projects

Lecture 6: SQL language is the romance language of data.

Lecture 7: Relational databases versus Non relational database

Lecture 8: Understand What is DBMS ?

Lecture 9: What is after data analysis?

Lecture 10: MySQL advantages and disadvantages

Lecture 11: MySQL installation on windows Machine

Lecture 12: install MySQL on MacOSx machine

Chapter 3: Your first MySQL Activity

Lecture 1: Learn how to Start, stop MySQL server using Command Prompt

Lecture 2: Learn how to Import external database to MySQL server

Chapter 4: App 2 ( Pele versus Maradona ) Who was better?

Lecture 1: Learn how to Create database and tables , columns and inserting data

Lecture 2: Use MySQL query to know which scored goals per game over 50%

Chapter 5: App 3 ( MySQL data types )

Lecture 1: Understand data types and the difference between Float and Decimal

Chapter 6: App 4 ( Select Statement in MySQL )

Lecture 1: Understand how select statement works and the order to retrieve data

Chapter 7: App 5 ( MySQL alter table )

Lecture 1: Understand how to add , delete , rename and modify MySQL tables

Chapter 8: App 6 ( primary and foreign key )

Lecture 1: The idea behind foreign and primary key in MySQL database

Lecture 2: Learn how to create relational tables using primary and foreign key

Chapter 9: App 7 ( MySQL where clause )

Lecture 1: Understand MySQL where clause

Chapter 10: App 8 ( ORDER BY clause )

Lecture 1: Sorting table columns Ascending Order or Descending order

Chapter 11: App 9 (MySQL Logical operators "AND" ,"OR" )

Lecture 1: Understand logical operators in MySQL like AND , OR , EQUAL , "NOT EQUAL"

Chapter 12: App 10 ( IN operator )

Lecture 1: Learn how to use range of values using "MySQL IN operator"

Chapter 13: App 11

Lecture 1: Understand "Date" variable and CAST from number to date .

Chapter 14: App 12 ( BETWEEN operator )

Lecture 1: Find  payments whose amount is between two values using "BETWEEN" operator

Chapter 15: App 13 ( Limit clause )

Lecture 1: Using LIMIT clause syntax with two arguments

Chapter 16: App 14 ( Joins )

Lecture 1: Use “JOIN” clause to find ONLY common fruits types

Chapter 17: App 15 ( joins )

Lecture 1: Continue use “JOIN” clause to find common fruits types

Chapter 18: MySQL aggregate functions

Lecture 1: Understand What is the benefit of Aggregate Functions in data analysis ?

Chapter 19: Project 1

Lecture 1: What you need before you start this project ?

Lecture 2: MySQL Business Case of DVD rental store

Chapter 20: Project 2

Lecture 1: Part1 : Investigate MySQL DB to help students in debt crisis

Lecture 2: Part 2 : Investigate MySQL DB to help students in debt crisis

Chapter 21: Project 3

Lecture 1: Which State in USA Has The Worst Drivers ?

Chapter 22: Bonus 1 : Introduction to NOSQL ( MongoDB )

Lecture 1: Understand Why Mongo DB in data analytics ?

Lecture 2: Understand What is the best language used for MongoDB ?

Lecture 3: Advantages and disadvantages of MongoDB

Lecture 4: Install Mongodb server on windows machine

Lecture 5: Install MongoDB on MacOSX

Lecture 6: Learn Write your first MongoDB query using JavaScript

Chapter 23: Project 4: data analysis project without programming

Lecture 1: Which state in USA Has The Worst Drivers ?

Chapter 24: Project 5: data analysis project without programming

Lecture 1: Statistical Analysis of the Work of Bob Ross

Chapter 25: Refresher : Data analysis introduction

Lecture 1: Refresher part

Lecture 2: Refresher: Is programming for data science easy or hard ?

Lecture 3: Refresher: Collection about important questions related to data science

Lecture 4: Refresher: Be patient for interview questions

Lecture 5: Refresher: People are panic from robot jobs

Chapter 26: Refresher : Data Analytics – Careers and robot jobs

Lecture 1: Refresher part

Lecture 2: Refresher: High demand for hiring data analysis engineer

Chapter 27: Refresher : Statistics for data analysis -Example about programming and big data

Lecture 1: Refresher part

Lecture 2: Refresher: Run your first SQL command without any previous experience

Lecture 3: Refresher: Note the difference between SQL and English language

Lecture 4: Refresher: What is big data ?

Lecture 5: Refresher: Professional answer about what is big data ?

Lecture 6: Refresher: What is OVERLOADS in a big data ?

Lecture 7: Understand 3'Vs ( Volume , variety , velocity ) in Big data

Chapter 28: Refresher : What is after data analysis ?

Lecture 1: Refresher: What is after data analysis ?