Statistics & Mathematics for Data Science & Data Analytics
What you’ll learn
- Master the fundamentals of statistics for data science & data analytics
- Master descriptive statistics & probability theory
- Machine learning methods like Decision Trees and Decision Forests
- Probability distributions such as Normal distribution, Poisson Distribution and more
- Hypothesis testing, p-value, type I & type II error
- Logistic Regressions, Multiple Linear Regression, Regression Trees
- Correlation, R-Square, RMSE, MAE, coefficient of determination and more
- Absolutely no previous experience required. We will learn everything right from the basics and then work our way up step by step
- Eagerness and motivation to learn
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 real-life 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 real-life examples you will learn the stats knowledge needed in a data scientist’s or data analyst’s career very quickly.
Who this course is for:
- Anybody that wants to master statistics & probabilities for data science & data analysis
- Anybody who wants to pursue a career in Data Science
- Professionals and students who want to understand the necessary statistics for data analysis
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