Udemy

Regression, Data Mining, Text Mining, Forecasting using R

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  • 4,760 Students
  • Updated 8/2018
4.5
(549 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
ExcelR EdTech
Rating
4.5
(549 Ratings)
3 views

Course Overview

Regression, Data Mining, Text Mining, Forecasting using R

Learn Regression Techniques, Data Mining, Forecasting, Text Mining using R

Data Science using R is designed to cover majority of the capabilities of R from Analytics & Data Science perspective, which includes the following:

  • Learn about the basic statistics, including measures of central tendency, dispersion, skewness, kurtosis, graphical representation, probability, probability distribution, etc.
  • Learn about scatter diagram, correlation coefficient, confidence interval, Z distribution & t distribution, which are all required for Linear Regression understanding
  • Learn about the usage of R for building Regression models
  • Learn about the K-Means clustering algorithm & how to use R to accomplish the same
  • Learn about the science behind text mining, word cloud, sentiment analysis & accomplish the same using R
  • Learn about Forecasting models including AR, MA, ES, ARMA, ARIMA, etc., and how to accomplish the same using R
  • Learn about Logistic Regression & how to accomplish the same using R

Course Content

  • 10 section(s)
  • 181 lecture(s)
  • Section 1 Introduction To Data Science
  • Section 2 Basic Statistics
  • Section 3 Hypothesis Testing Introduction
  • Section 4 Hypothesis Testing- Parametric
  • Section 5 Hypothesis Testing-Non Parametric
  • Section 6 BASICS OF R-PROGRAMMING
  • Section 7 Predictive Analytics
  • Section 8 Data Mining/Clustering Using R
  • Section 9 Clustering on Mixed Data
  • Section 10 High Dimension Data Analysis - Dimension Reduction

What You’ll Learn

  • Learn about the basic statistics, including measures of central tendency, dispersion, skewness, kurtosis, graphical representation, probability, probability distribution, etc.
  • Learn about scatter diagram, correlation coefficient, confidence interval, Z distribution & t distribution, which are all required for Linear Regression understanding
  • Learn about the usage of R for building Linear Regression
  • Learn about the K-Means clustering algorithm & how to use R to accomplish this
  • Learn about the science behind text mining, word cloud & sentiment analysis & accomplish the same using R

Reviews

  • K
    Khushbu Pawar
    5.0

    EXCELLENT LEARNING

  • M
    Mooktzeng Lim
    4.0

    Took some time to get use to the accent, but the content of the online course is mind blowing & amazing.

  • H
    Hari Shankar
    5.0

    overall good...course is very useful and the pace of teaching is simply super and is worth for every penny

  • S
    Shawn Alexander
    5.0

    Really good analysis techniques for forecasting as well as marketing

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