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Courses

Introduction to Data Science using R
Free

Introduction to Data Science using R

Overview

 R is rapidly becoming the leading language in data science and statistics. Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs.

This introduction to R programming course will help you master the basics of R. In seven sections, you will cover its basic syntax, making you ready to undertake your own first data analysis using R. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.

You will continuously practice your newly acquired skills through interactive in-browser coding challenges using the DataCamp platform. Instead of passively watching videos, you will solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.

What you'll learn

  • Introductory R language fundamentals and basic syntax
  • What R is and how it’s used to perform data analysis
  • Become familiar with the major R data structures
  • Create your own visualizations using R

DATA OBJECTS

  • Data types
  • Double
  • Integer
  • Complex
  • Logical
  • Character
  • Factor
  • Dates and Times
  • Missing data and Infinite values
  • Data structures
  • Vectors
  • Matrices
  • Arrays
  • Data frames
  • Time-series objects
  • List
  • The str function

IMPORTING DATA

  • Text files
  • Excel files
  • Databases
  • The Foreign package

DATA MANIPULATION

  • Vector subscripts
  • Matrix subscripts
  • Manipulating Data frames
  • Attributes
  • Character manipulation
  • Creating factors from continuous data
 

WRITING FUNCTIONS

  • Introduction
  • Arguments and variables
  • Control flow
  • Debugging your R functions

EFFICIENT CALCULATIONS

  • Vectorized computations
  • The apply and outer functions
  • Using Compiled code

GRAPHICS

  • More plot functions
  • Modifying a graph
  • Trellis Graphics
  • The ggplot2 package

STATISTICS

  • Basic statistical functions
  • Regression models
  • Linear regression models
  • Logistic regression
  • Tree models
  • Survival analysis
  • Non linear regression

 

OBJECT ORIENTED PROGRAMMING

R Language objects

About us

Bluebell Research Australia Pty. Ltd. is an Australian Startup engaged in training and placing candidates across Australia.

Contact Us

Email: training@bluebellresearch.com.au

Ph: +61 457298829/416769207

Address: 79 George Street, Parramatta, NSW, Australia

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