A ten-week program covering how to use R to apply fundamentals of statistical analysis and machine learning.
R is an open source programming language and software environment increasingly popular with statisticians, data scientists and decision makers. While a fully-fledged programming language that can take years to master, a fundamental understanding of R, its packages and development environments offers many opportunities. Students in the program will learn how to describe data, compare groups, cluster observations, identify association rules, build regression models, build classification models, and reduce feature spaces. The focus will be on developing an understanding of R, the R environment and relevant packages so that the student will become comfortable with exploring the R ecosystem. In all cases, students will be introduced to the theory, presented with real world examples and then assigned supervised hands-on tutorials.
The program is ideally suited for business professionals with basic statistical and computer literacy who wish to meet the growing demand for leaders with an analytical skillset. The program is also beneficial to those interested in a career in data science but who wish to learn more before enrolling in a master’s program. Students are asked to bring their personal laptop computers to class (either Mac OS or Windows). Students must have administrator rights to their laptops in order to successfully install and use the software used in the program.
Students in this program will be able to:
- Use R and a development environment such as R Studio to create and execute scripts in R
- Comfortably apply R’s various data structures such as vectors, matrices, data frames, etc., including application of subsetting techniques to isolate key components of data
- Import data from a variety of data sources including plain text files, CSV files, spreadsheets, SPSS files, SAS files etc.
- Work with imported data to ensure that it is in a form that can be explored, analyzed, modeled upon, etc.
- Confidently calculate and display the most important types of statistical summary information
- Graph data using R’s base packages as well as more advanced and powerful packages such as ggplot
- Generate a variety of statistical (machine learning) models such as regression, classification, clustering, and others
- Demonstrate through numeric data and graphical displays the validity of statistical models
- Produce reports based on statistical exploration, analyses, and modeling that can be exported to a variety of formats including PDFs, word processing documents, and the web
For a complete program description,
download the program's brochure.
Autumn Quarter 2021:
There is currently no scheduled session for this program.
Autumn Quarter 2021
Full payment of tuition must be received before the start of the program. Students who elect to pay tuition using a credit or debit card will be assessed a non-refundable 2.75% convenience fee.
Refund/Cancellation Policy: DePaul reserves the right to cancel any program before that program's first scheduled meeting, in which case tuition fees (but not convenience fees) will be refunded. The university's refund policy allows a return of 100% of tuition if the student drops the Fundamentals of Statistics and Machine Learning Using R Program within the first two weeks of the program (convenience fees will not be refunded).
Notice for Current DePaul Students
- Undergraduates: Please be aware that the tuition fee for this program is not included in the university’s full-time term package pricing.
Each program requires a $40.00 (non-refundable) application fee that can be paid online (via credit card) during the online application process. If you need to pay this fee by check or money order, please make the check or money order payable to DePaul University and send it to:
DePaul University Institute for Professional Development
243 S. Wabash Avenue
Chicago, IL 60604
Textbooks are a separate purchase to be made by students.
Reading materials for certificate programs consist of textbooks and supplementary handouts. Textbook readings are considered preparatory in nature and are typically assigned prior to lectures; supplementary handouts are frequently distributed in class to provide additional information.
There are no required textbooks for this session.
Fees are payable by check made out to DePaul University, or by credit card. Students who elect to pay tuition using a credit or debit card will be assessed a non-redundable 2.75% convenience fee.
Applicants who are eligible for a tuition reimbursement program offered by their employer and are interested in deferring their tuition payment using the university's Employer Tuition Deferral Plan must return the Employer Tuition Deferral Plan application to the Institute for Professional Development Office. Submitting this application to any other DePaul office may delay the student's registration process. Information about this plan, along with an application form, is found
Applicants who wish to use the university's Single Term Payment Plan or a third-party billing arrangement should contact the Institute for Professional Development office at (312) 362-6282 for details.
The Institute for Professional Development is pleased to announce a new need-based financial award, the
Chou Family IPD Scholarship, to provide funding for students interested in our certificate programs.
Applicants should have basic experience using a personal computer running Windows; no prior programming experience is necessary. Applicants should also possess basic statistical knowledge.
The Fundamentals of Statistics and Machine Learning Using R Program is catalogued as a non-credit course of DePaul University. A certificate of completion from DePaul University is awarded to those who successfully complete the program's requirements. Program requirements include in-class lab work as well as homework assignments. No midterm or final exams are conducted.
Course #: IPD 338
The Fundamentals of Statistics and Machine Learning Using R Program is a graded course. A final grade letter as well as DePaul transcript (upon request) will be available upon program completion.
Application & Registration Procedure
All interested parties should apply for admission using the Institute for Professional Development's
Application Form and email the completed form to email@example.com. Upon admission, the Institute office will contact the prospective student with information and instructions about the registration process.
You do not have to be an existing DePaul student to take this certificate program. Registration is restricted to individuals who apply for admission to the program and receive an acceptance letter. IPD staff will register applicants upon receipt of payment and registration form.
Regular DePaul students cannot register themselves via the university's registration system. If interested in enrollment, regular DePaul students should begin by submitting an application for admission. Students must meet the program's admission criteria.