MySQL and Applied statistics for Data Science Course resources

Section 1: Course Orientation

Section 2: An Introduction to SQL - MySQL - Data Science

Section 3: Your first MySQL Activity

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

Section 5: App 3 ( MySQL data types )

Section 6: App 4 ( Select Statement in MySQL )

Section 7: App 5 ( MySQL alter table )

Section 8: App 6 ( primary and foreign key )

Section 9: App 7 ( MySQL where clause )

Section 10: App 8 ( ORDER BY clause )

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

Section 12: App 10 ( IN operator )

Section 13: App 11

Section 14: App 12 ( BETWEEN operator )

Section 15: App 13 ( Limit clause )

Section 16: App 14 ( Joins )

Section 17: App 15 ( joins )

Section 18: MySQL aggregate functions

Section 19: Project 1

Section 20: Project 2

Section 21: Project 3

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

Section 23: Project Worst drivers in USA without programming

Section 24: Project 5 Statistical analysis of Bob Ross without programming

Section 25: Refresher : Data analysis introduction

Section 26: Refresher : Data Analytics - Careers and robot jobs

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

Section 28: Refresher : What is after data analysis ?

Section 29: Refresher : Start Descriptive statistics

Section 30: Refresher : Comparison between inferential and descriptive statistics

Section 31: Refresher : FAQ about descriptive statistics

Section 32: Refresher: Data types

Section 33: Refresher: Center of numerical data

Section 34: Refresher: Why center of the data is very important ?

Section 35: Refresher: Data dispersion and spread

Section 36: Refresher: Which one is better ? Standard deviation or range ?

Section 37: Refresher: Data shape

Section 38: Refresher: Outlier

Section 39: Refresher: Normal distribution lesson 1

Section 40: Refresher: Normal distribution lesson 2

Section 41: Start Inferential statistics ( Sampling distribution )

Section 42: Continue Sampling distribution

Section 43: Confidence interval and level part 1 lesson

Section 44: Confidence interval part 2

Section 45: Student's t distribution

Section 46: Examples about confidence interval

Section 47: Use Excel to calculate confidence interval

Section 48: Inferential Statistics : TAKE YOUR BREATH BEFORE HYPOTHESIS TESTING

Section 49: Calculate P value manual method

Section 50: Use Excel to calculate P value

Section 51: Mini story part 2 ( Two tailed t test )

Section 52: Understanding two tail test results in Excel

Section 53: Practical significance and statistical significance

Section 54: Bonus 2 ( Machine learning introduction )