Course Information
Course Overview
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
- 17 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
- Section 11 Relationship Mining - Association Rules
- Section 12 Recommendation System
- Section 13 Text Mining Using R
- Section 14 Forecasting Using XL Miner
- Section 15 Bonus: Forecasting Model Based Approaches
- Section 16 Bonus: Forecasting Data Driven Approaches
- Section 17 Interview Q&A's
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
Skills covered in this course
Reviews
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DDaniel Alfredo Chinchilla Leiva
Dificulty in the use of the resources
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KKhushbu Pawar
EXCELLENT LEARNING
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MMooktzeng Lim
Took some time to get use to the accent, but the content of the online course is mind blowing & amazing.
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HHari Shankar
overall good...course is very useful and the pace of teaching is simply super and is worth for every penny