Introduction to R Programming

In this R training course, students learn to program by diving into the R language and then use their new-found skills to solve practical data science problems. They'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write functions, and use all of R's programming tools.

Goals
  1. Work hands-on with three practical data analysis projects based on casino games.
  2. Store, retrieve, and change data values in your computer's memory.
  3. Write programs and simulations that outperform those written by typical R users.
  4. Use R programming tools such as if else statements, for loops, and S3 classes.
  5. Learn how to write lightning-fast vectorized R code.
  6. Take advantage of R's package system and debugging tools.
  7. Practice and apply R programming concepts as you learn them.
Outline
  1. Project 1: Weighted Dice
    1. The Very Basics
      1. The R User Interface
      2. Objects
      3. Functions
      4. Sample with Replacement
      5. Writing Your Own Functions
      6. Arguments
      7. Scripts
    2. Packages and Help Pages
      1. Packages
        1. install.packages
        2. library
      2. Getting Help with Help Pages
      3. Parts of a Help Page
  2. Project 2: Playing Cards
    1. R Objects
      1. Atomic Vectors
        1. Doubles
        2. Integers
        3. Characters
        4. Logicals
        5. Complex and Raw
      2. Attributes
        1. Names
        2. Dim
      3. Matrices
      4. Arrays
      5. Class
        1. Dates and Times
        2. Factors
      6. Coercion
      7. Lists
      8. Data Frames
    2. Loading Data
    3. Saving Data
    4. R Notation
      1. Selecting Values
        1. Positive Integers
        2. Negative Integers
        3. Zero
        4. Blank Spaces
        5. Logical Values
        6. Names
      2. Deal a Card
      3. Shuffle the Deck
      4. Dollar Signs and Double Brackets
    5. Modifying Values
      1. Changing Values in Place
      2. Logical Subsetting
        1. Logical Tests
        2. Boolean Operators
      3. Missing Information
        1. na.rm
        2. is.na
    6. Environments
      1. Environments
      2. Working with Environments
        1. The Active Environment
      3. Scoping Rules
      4. Assignment
      5. Evaluation
      6. Closures
  3. Project 3: Slot Machine
    1. Programs
      1. Strategy
        1. Sequential Steps
        2. Parallel Cases
      2. if Statements
      3. else Statements
      4. Lookup Tables
      5. Code Comments
      6. S3
      7. The S3 System
      8. Attributes
      9. Generic Functions
      10. Methods
        1. Method Dispatch
      11. Classes
      12. S3 and Debugging
      13. S4 and R5
    2. Loops
      1. Expected Values
      2. expand.grid
      3. for Loops
      4. while Loops
      5. repeat Loops
    3. Speed
      1. Vectorized Code
      2. How to Write Vectorized Code
      3. How to Write Fast for Loops in R
      4. Vectorized Code in Practice
      5. Loops Versus Vectorized Code
    4. Installing R and RStudio
      1. How to Download and Install R
        1. Windows
        2. Mac
        3. Linux
      2. Using R
      3. RStudio
      4. Opening R
    5. R Packages
      1. Installing Packages
      2. Loading Packages
    6. Updating R and Its Packages
      1. R Packages
    7. Loading and Saving Data in R
      1. Data Sets in Base R
      2. Working Directory
      3. Plain-text Files
        1. read.table
          1. sep
          2. header
          3. na.strings
          4. skip and nrow
          5. stringsAsFactors
        2. The read Family
        3. read.fwf
        4. HTML Links
        5. Saving Plain-Text Files
        6. Compressing Files
      4. R Files
        1. Saving R Files
      5. Excel Spreadsheets
        1. Export from Excel
        2. Copy and Paste
        3. XLConnect
        4. Reading Spreadsheets
        5. Writing Spreadsheets
      6. Loading Files from Other Programs
        1. Connecting to Databases
    8. Debugging R Code
      1. traceback
      2. browser
      3. Break Points
      4. debug
      5. trace
      6. recover
Class Materials

Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.

Preparing for Class

Training for your Team

Length: 3 Days
  • Private Class for your Team
  • Online or On-location
  • Customizable
  • Expert Instructors

Training for Yourself

$1,425.00 or 3 vouchers
  • Live Online Training
  • For Individuals
  • Expert Instructors
  • Guaranteed to Run
  • 100% Free Re-take Option
  • 1-minute Video

What people say about our training

Excellent trainer! She understands the material and how to teach it. Very impressed.
Ben Peacock
Academic Travel Abroad
In four days this course provided me with the essential tools I needed to do my job well and a wealth of resources at my fingertips as I grow as a web administrator. The interactive learning style is great, I would absolutely take a course with Webucator in the future!
Andrea Shaw
The Alliance
Fantastic instructors! The one I had was knowledgeable, professional and caring. He insured that every student's questions were answered in a manner that they understood. The environment set by the instructor made this one of my best learning experiences in my life!
Daniel Hansen
Leidos
I've never worked with SQL. The instructor did a great job in giving me a foundation to launch from.
Jeanne Vickery
Insight (KY)

No cancelation for low enrollment

Certified Microsoft Partner

Registered Education Provider (R.E.P.)

GSA schedule pricing

60,501

Students who have taken Instructor-led Training

11,679

Organizations who trust Webucator for their Instructor-led training needs

100%

Satisfaction guarantee and retake option

9.72

Students rated our Introduction to R Programming trainers 9.72 out of 10 based on 4 reviews

Contact Us or call 1-877-932-8228