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Statistics for Data Science - Probability and Statistics Tutorial

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Overview

One of the most critical aspects of the data science approach is our perception of getting the information processed. In developing insights from our accumulated data, we dig out the possibilities. And those possibilities are known as statistical analysis in Data science.

Statistics acts as a tool to gather, extract, analyze, and review data, which is an input to Data science techniques; hence, learning statistics is a baby step toward becoming a data scientist. Great Learning‘s Statistics for Data Science course is for beginners and professionals who want to upgrade their skills in data science domains and learn everything about statistical analysis.

Syllabus

Introduction - .
1. Statistics vs Machine Learning - .
2. Types of Statistics [Descriptive, Prescriptive and Predictive - .
3. Types of Data - .
4. Correlation – .
5. Covariance – .
6. Introduction to Probability – .
7. Conditional Probability with Baye’s Theorem – .
8. Binomial Distribution – .
9. Poisson Distribution – .

Taught by

Great Learning

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