DESCRIPTION
● 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.
● 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.
WHAT YOU WILL 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
WHO THIS BOOK IS FOR
● Anyone that is looking for a complete and comprehensive intro to Power BI
● Everyone that wants to also learn more advanced Power BI skills such as DAX for calculated columns and measures
● Anyone that wants to pursue a career as a data analyst, data scientist or BI consultant
● Anyone that has never used Power BI before and is looking for a hands-on approach to learn it
