This is the bite size course to learn Python Programming for Applied Statistics. In CRISP DM data mining process, Applied Statistics is at the Data Understanding stage. This course also covers Data processing, which is at the Data Preparation Stage. 

You will need to know some Python programming, and you can learn Python programming from my "Create Your Calculator: Learn Python Programming Basics Fast" course.  You will learn Python Programming for applied statistics.

You can take the course as follows, and you can take a exam at EMHAcademy to get SVBook Certified Data Miner using Python certificate : 

- Create Your Calculator: Learn Python Programming Basics Fast (R Basics)

- Applied Statistics using Python with Data Processing (Data Understanding and Data Preparation)

- Advanced Data Visualizations using Python with Data Processing (Data Understanding and Data Preparation, in future)

- Machine Learning with Python (Modeling and Evaluation)

Content

1. Getting Started

2. Getting Started 2

3. Getting Started 3

4. Data Mining Process

5. Download Data set

6. Read Data set

7. Mode

8. Median

9. Mean

10. Range

11. Range One Column

12. Qunatile

13. Variance

14. Standard Deviation

15. Histogram

16. QQPLot

17. Shapiro Test

18. Skewness and Kurtosis

19. Describe()

20. Correlation

21. Covariance

22. One Sample T Test

23. Two Sample TTest

24. Chi Square Test

25. One Way ANOVA

26. Simple Linear Regression

27. Multiple LInear Regression

28. Data Processing: DF.head()

29. Data Processing: DF.tail()

30. Data Processing: DF.describe()

31. Data Processing: Select Variables

32. Data Processing: Select Rows

33. Data Processing: Select Variables and Rows

34. Data Processing: Remove Variables

35. Data Processing: Append Rows

36. Data Processing: Sort Variables

37. Data Processing: Rename Variables

38. Data Processing: GroupBY

39. Data Processing: Remove Missing Values

40. Data Processing: Is THere Missing Values

41. Data Processing: Replace Missing Values

42. Data Processing: Remove Duplicates