Regression, Data Mining, Text Mining, Forecasting using R

Course Description

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

What are the requirements?

  • Download R & RStudio before starting this tutorial
  • Download datasets folder in zipfile which is uploaded in session 1

What am I going to get from this course?

  • 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

Who is the target audience?

  • All the IT professionals, whose experience ranges from ‘0’ onwards are eligible to take this session. Especially professionals from data analysis, data warehouse, data mining, business intelligence, reporting, data science, etc, will naturally fit in well to take this course.

Full Details : [ Take Course Now ]
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