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Introduction to R Programming

Ascendient Learning's Introduction to R Programming training course teaches attendees how to use R programming to explore data from a variety of sources by building inferential models and generating...

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By Request
$3,020 USD
Duration 4 days
Course Code ACCEL-R-INTRO
Available Formats Classroom

Overview

Ascendient Learning's Introduction to R Programming training course teaches attendees how to use R programming to explore data from a variety of sources by building inferential models and generating charts, graphs, and other data representations.

Skills Gained

  • Master the use of the R and RStudio interactive environment
  • Expand R by installing R packages
  • Explore and understand how to use the R documentation
  • Read Structured Data into R from various sources
  • Understand the different data types in R
  • Understand the different data structures in R
  • Understand how to create and manipulate dates in R
  • Use the tidyverse collection of packages to manipulate dataframes
  • Write user-defined R functions
  • Use control statements
  • Write Loop constructs in R
  • Use the apply family of functions to iterate functions across data
  • Expand iteration and programming through the Purrr package
  • Reshape data from long to wide and back to support different analyses
  • Perform merge operations with R
  • Understand split-apply-combine (group-wise operations) in R
  • Identify and deal with missing data
  • Manipulate strings in R
  • Understand basic regular expressions in R
  • Understand base R graphics
  • Focus on GGplot2 graphics for R for generating charts
  • Use RMarkdown to programmatically generate reproducible reports
  • Use R for descriptive statistics
  • Use R for inferential statistics
  • Write multivariate models in R (general linear models)
  • Understand confounding and adjustment in multivariate models
  • Understand interaction in multivariate models
  • Predict/Score new data using models
  • Understand basic non-linear functions in models
  • Understand how to link data, statistical methods, and actionable questions

Prerequisites

Students should have knowledge of basic statistics (t-test, chi-square-test, regression) and know the difference between descriptive and inferential statistics. No programming experience is needed.

Course Details

Training Materials

All attendees receive comprehensive courseware and a textbook.

Software Requirements

  • A recent release of R 4.x
  • IDE or text editor of your choice (RStudio recommended)

Outline

  • Overview
    • History of R
    • Advantages and disadvantages
    • Downloading and installing
    • How to find documentation
  • Introduction
    • Using the R console and RStudio
    • Getting help
    • Learning about the environment
    • Writing and executing scripts
    • Object oriented programming
    • Introduction to vectorized calculations
    • Introduction to data frames
    • Installing and loading packages
    • Working directory
    • Saving your work
  • Variable types and data structures in base R
    • Variables and assignment
    • Data types
      • Numeric, character, boolean, and factors
    • Data structures
      • Vectors, matrices, arrays, dataframes, lists
    • Indexing, subsetting
    • Assigning new values
    • Viewing data and summaries
    • Naming conventions
    • Objects
  • Getting data into the R environment with readr
    • Built-in data
    • Reading data from structured text files
    • Reading data using ODBC
  • Dataframe manipulation with dplyr
    • Introduction to tibbles, enhanced data frames
    • Renaming columns
    • Adding new columns
    • Binning data (continuous to categorical)
    • Combining categorical values
    • Transforming variables
    • Handling missing data
    • Merging datasets together
    • Stacking datasets together (concatenation)
  • Handling dates in R using lubridate
    • Date and date-time classes in R
    • Formatting dates for modeling
  • Exploratory data analysis (descriptive statistics)
    • Continuous data
      • Distributions
      • Quantiles, mean
      • Bi-modal distributions
      • Histograms, box-plots
    • Categorical data
      • Tables
      • Barplots
    • Group by calculations with dplyr
      • Split-apply-combine
    • Reshaping and pivoting data in R (long to wide with aggregation)
      • pivot_wider and _longer with tidyr
  • Working with text data
    • Finding and matching patterns in text
    • Stringr package for text manipulation
    • Introduction to regular expressions in R
    • Categorical data wrangling with forcats
  • Control flow
    • Truth testing
    • Branching
    • Looping
  • Functions in depth
    • Parameters
    • Return values
    • Variable scope
    • Exception handling
  • Applying functions across dimensions
    • Sapply, lapply, apply
    • Programming with map and purrr
  • Graphics in R Overview
    • Base graphics system in R
    • Scatterplots, histograms, barcharts, box and whiskers, dotplots
    • Labels, legends, titles, axes
    • Exporting graphics to different formats
  • Advanced R graphics: ggplot2
    • Understanding the grammar of graphics
    • Quick plots (qplot function)
    • Building graphics by pieces (ggplot function)
    • Understanding geoms (geometries)
    • Linking chart elements to variable values
    • Controlling legends and axes
    • Exporting graphics
  • Inferential Statistics
    • Bivariate correlation
    • T-test and non-parametric equivalents
    • Chi-squared test
  • General Linear Regression Models in R
    • Understanding formulas
    • Linear and logistic regression models
    • Regression plots
    • Confounding / interaction in regression
    • Evaluating residuals
    • Scoring new data from models (prediction)
    • Useful plots from regression models
  • Conclusion
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Schedule

Upcoming Course Dates

There are currently no scheduled dates for this course. If you are interested in this course, contact us with the form below.

Contact Information

FAQ

Does the course schedule include a Lunchbreak?

Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does Ascendient Learning deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

What does vendor-authorized training mean?

As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.

Is the training too basic, or will you go deep into technology?

It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.

How up-to-date are your courses and support materials?

We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.

Are your instructors seasoned trainers who have deep knowledge of the training topic?

Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.

Do you provide hands-on training and exercises in an actual lab environment?

Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.

Will you customize the training for our company’s specific needs and goals?

We will work with you to identify training needs and areas of growth.  We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.

How do I get started with certification?

Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.

Will I get access to content after I complete a course?

You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.

How do I request a W9 for Ascendient Learning?

View our filing status and how to request a W9.

Reviews

Topics, material and specially instructor (Graham Godfrey) was beyond my expectations.

This course gave me a clearer understanding of the AWS cloud architecture.

The class and material is good. I think some of the software needs to be updated.

the class/lecture was amazing and very easy to understand and was in detail.

Class was very informative, although one lab didnt but will try again later