IRPUndergraduate courses
Introduction to R Programming
An easy first course in R for people with little or no programming experience — syntax, loops, vectors and data frames, written from scratch.
- Introductory
- 4 weeks
- Approx. 15 hours per week
- 3 semester hours
About this course
This course provides an easy introduction to programming in R for those who have little or no programming experience. It starts before R does: what a file format is, what pseudocode and a flow chart are for, and which text editor to write code in. From there it covers basic R syntax, reading data files, symbols and assignment, simple loops, and the data structures you will spend the rest of your R career using — vectors, lists, matrices and data frames, and how to subset each of them. By the end you can load a data set, manipulate it, and produce numerical summaries and basic graphs.
Who this course is for
Anyone who wants to start studying programming in R, especially people with no prior programming experience of any kind. Analysts, researchers and students who have been reading other people's R code and now need to write their own will find this the place to begin.
What you will learn
12 outcomes
By the end of this course, you will be able to:
- Install R and RStudio
- Write simple pseudocode and create flow charts
- Document code
- Use file management and version control tools
- Perform simple arithmetic and statistical operations in R
- Read data files into R
- Create loops for iteration
- Subset data vectors and lists
- Use the apply family of functions for subsetting and computation
- Use simple R functions for numerical analysis and basic graphs
- Work confidently with R data structures, especially vectors and data frames
- Manipulate, sort and merge data frames
Week by week
4-Week curriculum overview
This curriculum is identical across all start dates. Expand a week to explore the topics covered.
- Weeks
- 4
- Your week
- Approx. 15 hours
- Level
- Introductory
Getting started with RWeek 1
- Basic programming principles — flow charts and pseudocode
- Installing, starting and stopping R
- File operations and file formats
- Writing code and text editors
- Basic R syntax
- Reading files
- Symbols and assignment
Variables, loops and data structuresWeek 2
- Variables
- Sequences
- Simple loops — iteration
- Data structures
- Exploring data
- Subsetting data
apply and other functionsWeek 3
- The apply function
- Special values
- Packages
- Useful functions
Multidimensional dataWeek 4
- Overview of vectors and vector manipulation
- Factors
- Attributes
- Lists, matrices and arrays
- Data frames
Instructors
Expert-Led Guidance
Each cohort is led by dedicated instructors and assistant teachers who actively lead weekly discussions, provide personalized feedback and grade your assignments.
Mr. Kuber Deokar
Mr. Kuber Deokar is Data Science Lead at UpThink EduTech Services. He holds a master's degree in Statistics from the University of Pune, India, where he previously taught undergraduate statistics. He co-authored Machine Learning for Business Analytics with Galit Shmueli, Peter Bruce and Nitin Patel. With over a decade of experience, he specializes in course design, development, delivery and management, coordinating online courses and the communication between course creators, instructors, teaching assistants and students. His interests are machine learning and responsible artificial intelligence.
Before you start
What you need
Everything you need to have on hand before the first week. Open a row for the detail.
Course Format & Schedule
This is a 4-week, 100% online, asynchronous course.
- No mandatory live sessions: Log in and complete your work at times that fit your schedule.
- Weekly Releases: At the start of each week, you will receive new lecture materials and answer keys for the previous week's exercises.
- Interactive Community: Work through exercises, submit assignments, and engage with your instructor and peers via a private discussion board.
Homework
Short-answer questions testing the concepts, guided exercises in writing code, and guided data analysis problems using software.
Texts
The course text is Introduction to Data Technologies by Paul Murrell. It may be purchased from the publisher Chapman and Hall/CRC Press. The text is also available online here in both PDF and HTML formats.
Software
You need a copy of R, which is free from r-project.org, and RStudio, which is the editor used throughout. Installation is covered in week one, but try it before the course starts so that any problem with your machine is found early rather than in the middle of the first assignment.
Course dates
2026
11/02/2026to12/02/2026
Instructors: Mr. Kuber Deokar
12/07/2026to01/04/2027
Instructors: Mr. Kuber Deokar
10/05/2026to11/05/2026
Instructors: Mr. Kuber Deokar
Enrollment closed
Refund policy
Refund: $550 before start, $325 until day 7, none after. Date changes: first one free, then $25 each, until day 7. Full terms
FAQ
I have never written a line of code in any language. Is that a problem?This course
No — that is who the course is written for. Week one deliberately spends its time on the things a first programming course usually assumes: what a file format is, how to sketch a procedure as pseudocode or a flow chart, and how to get code out of your head and into an editor. R itself comes next.
Do I need to install anything before the first week?This course
Installing R and RStudio is part of week one, so nothing is required in advance. Attempting the installation beforehand is still worth doing: it is free, it takes a few minutes, and if your machine puts up a fight you will have found out while there is time to sort it out.
Is there a money-back or satisfaction guarantee?Every course
Before your course starts, you get back what you paid minus a $100 processing fee. After it starts, until the deadline, which is the end of day 7 after the start date (for some courses, the end of the 10th of the month the course starts instead), you get back 50% of what you paid. After the deadline there is no refund. To ask, use the withdrawal form in your account or email support@learnstatistics.org. A person reviews every request.
Can I transfer to a later start date or withdraw after the course begins?Every course
Yes. You can move to another start date of the same course yourself, from My learning, until its move deadline (by default the end of day 7 after the start date). The first move of each course is free, and each later one costs $25. Withdrawing follows the refund rules above: 50% of what you paid until the deadline, and no refund after it. Moving does not restart the refund deadline: it is based on the earlier of the date you first bought and your new date.
How do I ask for a refund, and how long does it take?Every course
Use the withdrawal form in your account, or email support@learnstatistics.org. A person reviews every request: we reply within 2 business days and confirm the outcome within 5. Approved refunds go back to the card you paid with and usually arrive within 5 to 10 business days. The course then leaves your account and your classroom.
What if the course is cancelled?Every course
If we cancel your session, you choose: a full refund with no processing fee, or a free move to the next available date. The $25 fee for moving dates yourself is never refunded.
Who teaches the course?Every course
Each cohort is led by dedicated instructors and assistant teachers who actively lead weekly discussions, provide personalized feedback and grade your assignments. The instructor for each start date is listed on the course page.
Something not answered here? Ask us before you book — and the terms set out what a purchase covers.
Credit, and where it counts
This course carries a verified figure of 3 semester hours. A credit recommendation from the American Council on Education says what a course is worth; the institution receiving it decides whether to award it.
Anyone can take this subject: there is no application, and you do not have to be studying at a university. It also counts toward a degree at Thomas Edison State University in Trenton, New Jersey, which decides what to award for it. The course is taught online, so you take it the same way in New Jersey or anywhere else. The full position — including the limits each university publishes is on its own page, and worth reading before you buy.