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Course

Data Science using R + R Programming

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41 Lessons

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Course Materials

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Lessons

Introduction to R

Import / Export Data and Data Structures

Intro to Statistics

Data Exploration

Data Manipulation

Horizontal and Vertical Joins

Date, Time Functions

String Functions

Loops

Transpose Data, User Defined Function-I

User Defined Function-II

Data Visualization using ggplot2

R Programming Practice Material

Basics - Statistics

Hypothesis Testing

Chi-Square, Standardization, PCA- Part I

PCA - Part II and Hierarchical Variable Clustering

Cluster Analysis - Part I

Cluster Analysis - Part II

Cluster Analysis - Part III

Machine Learning Basics

Linear Regression - Part I

Linear Regression - Part II & Logistic Regression - Part I

Logistic Regression - Part II

Logistic Regression - Part III

Decision Tree

Random Forest

K Nearest Neighbor | PCA vs. Variable Clustering

Support Vector Machine (SVM)

Stochastic Gradient Boosting

Comparison of Supervised Learning Algorithms

Live Project

Live Project (R Programming)

Assignment : Churn Modeling

Interview Questions

Time Series - Theory

Time Series - R Code

Banking + PD Modeling

Intro to Text Mining

Basics of Text Mining with R - Part I

Basics of Text Mining with R - Part II

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