Statistics for Data Science - Probability and Statistics for Engineers

If you want to foray into the world of data science, you need to have good command over statistics. Statistical knowledge helps us use the proper methods to collect the data, employ the correct analysis, and effectively present the results. Statistics is a crucial process for making discoveries in science, make decisions based on data and making predictions.

Great Learning brings you this 12-hour intensive course on “Statistics for Data Science” which will help you to comprehensively learn all the basic and advanced topics essential in Statistics for Data Science. This in-depth course starts from a complete beginner perspective and introduces you to the various facets of statistics and concepts required to solve data science problems. You will learn how to apply these concepts to business problems. This course is taught by Dr. Abhinanda Sarkar, a PhD in Statistics from Stanford University.

- Introduction to Course.
- Agenda.
- Introduction to Statistics.
- Standard Deviation.
- Correlation and Covariation.
- Introduction to Probability.
- Hypothesis Testing.
- Marginal and Conditional Probability.
- Normal Distribution.
- Linear Regression.