Statistics & Mathematics for Data Science & Data Analytics
Statistics & Mathematics for Data Science & Data Analytics
Learn the statistics & probability for data science and business analysis
Created by Nikolai Schuler| 11.5 hours on-demand video course
This Statistics & Mathematics for Data Science & Data Analytics 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.
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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
