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R essentials for Data Scientists

Course Code: 1252
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$1995

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Overview

The R Essentials for Data Scientists training program enables participants to work with applications in OpenSource environments including the R language. R is a functional programming environment used commonly by data scientists and data analysts though it can be easily used by non-programmers as well. Either ways, working with R language is a much sought after skill for data analysts and data scientists. The course discusses using R with various libraries to effectively apply Spark/R and Sparkly/R. Participants will learn to come up with effective solutions to common real-life scenarios encountered when performing different analysis.

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Trivera

Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 5 days

Live Virtual Classroom
Duration: 5 days

What You'll learn

  • R language and mathematics
  • Working with R vectors
  • Reading and writing data from files, and categorizing data in factors
  • Working with dates and perform date math
  • Working with multiple dimensions and DataFrame essentials
  • Fundamentals of data science and how to use R with it
  • Visualization in R
  • Application of R in Spark

Outline

Module 1: From Excel to R

  • Common problems with Excel
  • The R environment
  • Hello, R
  • CRAN

Module 2: R Basics

  • Simple Math with R
  • Working with Vectors
  • Functions
  • Comments and code structure
  • Using packages

Module 3: Vectors

  • Vector properties
  • Creating, combining and iterating
  • Passing and returning vectors in functions
  • Logical vectors

Module 4: Reading and writing files

  • Working with dates
  • Date formats and formatting
  • Time manipulation and operations

Module 5: Multiple dimensions

  • Adding a second dimension
  • Indices and named rows and columns n a Matrix
  • Matrix calculations
  • n-Dimensional arrays
  • Data frames
  • Lists

Module 6: Overview of R in Data Science

  • AI grouping theory
  • K-means
  • Linear regression
  • Logistic regression
  • Elastic net

Module 7: Next steps

  • Powerful data through visualization: Communicating the message
  • R in Spark
  • Demos
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Prerequisites

Participants need to have familiarity with data analytics.

Who Should Attend

The course is highly recommended for –

  • Data scientists
  • Data analysts
  • Machine learning professionals

Interested in this course? Let’s connect!

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