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Data Analytics with R

Course Code

BD81

Duration

3 Days

Basic programming background is preferred.
R is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students. It covers language fundamentals, libraries and advanced data analytics and graphing with real world data.

Note: This is not a machine learning class. If you are looking for a Machine Learning class; please refer to Machine Learning Essentials.
This course is designed for Developers / data analysts.

In this course, participants will learn:

  • R language fundamentals
  • R data structures (Lists, Dataframes, Matrices)
  • Graphing with R
  • Advanced analytics With R

Language Basics
Introducing R Language
Variables and Types
Control Structures (Loops / Conditionals)
Vectors, Matrices and Arrays
String and text manipulation using stringr
Lists
Levels / Factors
Functions
apply functions
Labs for all sections

Intermediate R Programming
Dataframes
DataFrames and File I/O
Reading data from files
Data cleanup and preparation
Exploring built-in Datasets
Tidyverse packages – readr, tidyr, dplyr
Visualization

  • R-Graphics Package
  • ggplot2 package

Labs for all sections
Practice Lab: data analytics with tidyvserse

Advanced Analytics with R
Statistical Modeling
Covariance / Correlation / Covariance Matrix
Erros / Residuals
Feature Engineering
Distributions (Binomial, Poisson, Normal)
Text analytics – ngrams, context analytics
Regressions

  • Linear Regression
  • Logistic Regression

R and Big Data – Hadoop & Spark
Labs for all sections
Practice Labs


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