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Introduction to R for Data Scientists

Course Details
Code: TTCR01-DS3
Tuition (USD): $1,995.00 • Classroom (3 days)

Skills Gained

  • Introduction to the R Environment
  • Going from Excel to R
  • Simple math with R
  • How and when to use and apply vectors
  • Manipulating text
  • Formatting dates; manipulating time and operations
  • How to work with multiple dimensions
  • Working with R with Madlib / AI libraries
  • Techniques in Data Visualization

Who Can Benefit

While there are no specific technical prerequisites, students should have had prior exposure to working with statistics and probability, as well as good hands-on working knowledge of Excel. We will collaborate with you to design the best solution to ensure your needs are met, whether we customize the material, or devise a different educational path to help your team best prepare for this training.

Course Details

Session: From Excel to R

  • Common problems with Excel
  • The R Environment
  • Hello, R

Session: R Basics

  • Simple Math with R
  • Working with Vectors
  • Functions
  • Comments and Code Structure
  • Using Packages

Session: Vectors

  • Vector Properties
  • Creating, Combining, and Iterating
  • Passing and Returning Vectors in Functions
  • Logical Vectors

Session: Reading and Writing

  • Text Manipulation
  • Factors

Session: Dates

  • Working with Dates
  • Date Formats and formatting
  • Time Manipulation and Operations

Session: Multiple Dimensions

  • Adding a second dimension
  • Indices and named rows and columns in a Matrix
  • Matrix calculation
  • n-Dimensional Arrays
  • Data Frames
  • Lists

Session: R in Data Science

  • AI Grouping Theory
  • K-means
  • Linear Regression
  • Logistic Regression
  • Elastic Net

Session: R with MadLib

  • Importing and Exporting static Data (CSV, Excel)
  • Using Libraries with CRAN
  • K-means with Madlib
  • Regression with Madlib
  • Other libraries

Session: Data Visualization

  • Powerful Data through Visualization: Communicating the Message
  • Techniques in Data Visualization
  • Data Visualization Tools
  • Examples