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Advanced R

The Advanced R for Data Science is a 3-day intensive R training program designed to provide attendees with a comprehensive toolkit for applying R to business intelligence data solutions. The workshop is meant to offer a hands-on introduction to R and a set of data analysis methods for business analysts and other professionals that already possess an adequate knowledge of computer programming experience and in particular R programming experience. Attendees will benefit from exposure to a number of statistical learning and machine learning methods for data analysis. In particular, the workshop will cover statistical learning methodology, regression, and classification. The FedEx Institute is organizing this workshop to meet a critical need among corporations and nonprofits for a deep quantitative analysis toolkit designed to meet the rising big data challenges faced by all organizations.

Corporate Rate: $500/Attendee
Academic & Nonprofit: $300/Attendee


3 Days

Program Length

Upcoming Session

Scheduled by Demand

Join the Waitlist to be notified.

8:00AM - 4:30 PM

(Central Time Zone)

Virtual (Zoom) or In-Person by Request

Course Overview

Course Requirements

Attendees are required to have previous R programming experience. Familiarity with another programming language or platform (Python, C, MATLAB, etc.) language is an asset. The workshop is meant for professionals with previous programming experience.

Important: Attendees must bring their own device with the required R environment (correct version) and associated packages pre-installed. Click here for installation guidelines.

Course Rubric

Day 1

  • 8:30 – Introduction to Statistical Learning and Machine Learning, Quick Example, Estimating functions from data, supervised vs. unsupervised learning, Model Assessment

  • 10:00 – Break

  • 10:15 – Introduction to Simple Linear Regression - multiple linear regression, interaction factors, linear model selection and regularization

  • 11:45 – Lunch

  • 1:15 – Classification: Logistic Regression

  • 2:45 – Break

  • 3:00 – Classification: Linear Discriminant Analysis

  • 4:30 – Break

Day 2

  • 8:30 – Classification: Quadratic Discriminant Analysis

  • 10:00 – Break

  • 10:15 – Classification: Comparing Classification Methods

  • 11:45 – Lunch

  • 1:15 – Classification: Decision Trees

  • 2:45 – Break

  • 3:00 – Classification: Naïve Bayes

Day 3

  • 8:30 – Classification: Support Vector Machines

  • 10:00 – Break

  • 10:15 – Unsupervised Learning: K-Means

  • 11:45 – Lunch

  • 1:15 – Multiple linear regression, interaction factors, linear model selection and regularization

  • 2:45 – Break

  • 3:00 – Workshop Assessment

  • 4:30 – Break

Be the first to know when registration opens by joining our exclusive Training Notification List.

  • Early Access: Get priority access.

  • Stay Informed: Receive details about new sessions.

  • Limited Spots: Ensure you secure your spot.

No Upcoming Session?

All training classes are NONREFUNDABLE within 14 days of the training’s scheduled start date.


Attendees who wish to cancel within the 14-day nonrefundable period will need to email Rami Lotay ( and give a detailed explanation as to why they cannot possibly attend.


Attendees may still be liable for payment in full pending review from our staff.

Cancellation Policy
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