Statistics & Mathematics for Data Science & Data Analytics
 Description
 Curriculum
 FAQ
 Reviews
Are you aiming for a career in Data Science or Data Analytics?
Good news, you don’t need a Maths degree – this course is equipping you with the practical knowledge needed to master the necessary statistics.
It is very important if you want to become a Data Scientist or a Data Analyst to have a good knowledge in statistics & probability theory.
Sure, there is more to Data Science than only statistics. But still it plays an essential role to know these fundamentals ins statistics.
I know it is very hard to gain a strong foothold in these concepts just by yourself. Therefore I have created this course.
Why should you take this course?

This course is the one course you take in statistic that is equipping you with the actual knowledge you need in statistics if you work with data

This course is taught by an actual mathematician that is in the same time also working as a data scientist.

This course is balancing both: theory & practical reallife example.

After completing this course you ll have everything you need to master the fundamentals in statistics & probability need in data science or data analysis.
What is in this course?
This course is giving you the chance to systematically master the core concepts in statistics & probability, descriptive statistics, hypothesis testing, regression analysis, analysis of variance and some advance regression / machine learning methods such as logistics regressions, polynomial regressions , decision trees and more.
In reallife examples you will learn the stats knowledge needed in a data scientist’s or data analyst’s career very quickly.
If you feel like this sounds good to you, then take this chance to improve your skills und advance career by enrolling in this course.

29Intro

30Probability Basics

31Calculating Simple Probabilities

32Practice: Simple Probabilities

33Quick solution: Simple Probabilites

34Detailed solution: Simple Probabilities

35Rule of addition

36Practice: Rule of addition

37Quick solution: Rule of addition

38Detailed solution: Rule of addition

39Rule of multiplication

40Practice: Rule of multiplication

41Solution: Rule of multiplication

42Bayes Theorem

43Bayes Theorem  Practical example

44Expected value

45Practice: Expected value

46Solution: Expected value

47Law of Large Numbers

48Central Limit Theorem  Theory

49Central Limit Theorem  Intuition

50Central Limit Theorem  Challenge

51Central Limit Theorem  Exercise

52Central Limit Theorem  Solution

53Quiz: Bayes Theorem

54Binomial distribution

55Poisson distribtuion

56Real life problems

57Intro

58What is an hypothesis?

59Significance level and pvalue

60Type I and Type II errors

61Confidence intervals and margin of error

62Excursion: Calculating sample size & power

63Performing the hypothesis test

64Practice: Hypothesis test

65Solution: Hypothesis test

66ttest and tdistribution

67Proportion testing

68Important pz pairs

69Quiz: Hypothesis Testing

70Intro

71Linear Regression

72Correlation coefficient

73Practice: Correlation

74Solution: Correlation

75Practice: Linear Regression

76Solution: Linear Regression

77Residual, MSE & MAE

78Practice: MSE & MAE

79Solution: MSE & MAE

80Coefficient of determination

81Root Mean Square Error

82Practice: RMSE

83Solution: RMSE

84Quiz: Regression