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About this Course


This is the course I wish I had when I started as a graduate student. One can spend so much time designing experiments and collecting data and then have no idea how to explore and visualize those data.


The R learning curve does not have to be so difficult and long. In this course, I’ve carefully selected the key topics and functions that will help you master the basics and quickly get over the curve with confidence, even if you’re a complete beginner.


In truth, with only a few functions and methods in R you can do at least 80% of all the data wrangling and visualization you’ll ever need to do in ecology. This course focuses on those key concepts so your learning experience is as efficient as possible.


By the end of the course you will be able to confidently:
  • Install R and RStudio
  • Use RStudio like a pro
  • Upload your data into R
  • Clean and prepare data for plotting and analysis
  • Explore your data by adding new variables, combining datasets and modifying existing variables
  • Create publication-quality figures using scatterplots, line graphs, and boxplots
  • Manage and organize entire projects with R and RStudio
  • Learn the best practices for writing clear and reproducible code in R
In summary, this course is a shortcut to learning R quickly but effectively. Though most content is designed and presented from my own perspective as an ecologist, all course content is also applicable to most related fields.




What this course does not cover:
To cover the basics of R in an effective way, I cannot cover everything. So this course does not cover:
  • Data analysis or modeling
  • GIS or spatial visualization
  • Advanced topics in visualization such as using ggplot2
I believe that these topics are relatively easy to branch into once your foundation with the basics is in place and I plan to expand into these and other topics in future courses.



Scholarship Program
I also understand that this course may not be accessible to everyone depending on funds and economic situation in their country. It is part of my personal vision and mission that everyone has equal opportunities, so I created a scholarship program. For those who feel they can’t afford the course, please complete the short application by clicking here.



Enrollment is currently closed, but be sure to pre-register for updates to be the first to hear when this course is released again!


"Luka is perfect for teaching a course on R for budding ecologists—he has a strong theoretical background in ecology, numerous experiences in field- and greenhouse-based studies, a knack for data analyses, and a life-long passion to teach.

I highly recommend The Basics of R for Ecologists to undergraduate and graduate students involved in ecological research."

Dr. Nishanta RajakarunaAssociate Professor in Plant Biology, CalPoly State University

This course is closed for enrollment.

Portrait of Luka Negoita, PhD

Your instructor


Luka Negoita, PhD

I believe the fundamental beauty of the natural world comes from understanding the stories behind the patterns we see.

I received my PhD in Biology from Syracuse University in 2018 where I specialized in analyzing ecological data using R. I also love teaching and have mentored countless students and scientists in everything from experimental design to using R for creating figures for their publication. Have messy data? Let me help you clean it. Have some numbers? Let me help you tell your story.

Along with the academic skills and hacks I've learned along the way, I present The Grad Ecologist courses as my way of helping the next generation of grad students in ecology.

Course Curriculum


  1 Welcome to the course!
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  2 Introduction to R and RStudio
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  3 Vectors and Dataframes
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  4 Uploading Data
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  5 Basic Data Visualization
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  6 Data Wrangling 101
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  7 Advanced Data Wrangling
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  8 Organizing Projects
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  Congratulations!
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Frequently Asked Questions



When does the course start and finish?

The course is a completely self-paced online course, so you decide when you start and when you finish.


How long do I have access to the course?

How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own! But the enrollment period is only for one week!


What if I am unhappy with the course?

We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.


Can I get a certificate for completing this course?

Yes, absolutely! Everyone that completes this course will receive an official certificate of completion.


What if I'm not an ecologist? Is the course still relevant?

Yes! Though the course is based on my own experiences of using R for ecology, all of the course content will be applicable and relevant for most other fields in biology if not many fields even outside the sciences. The course also uses ecological datasets, but the principles are mostly universal.


Does it matter if I use a Mac or PC?

Nope! Although the course is taught using a Mac, the content and features in R and R Studio are universal between the two operating systems and I mention anytime there is a difference between the two.


But what if I don't know anything about R or statistics?

That's fine! This course is designed as the first step for anyone interested in learning how to use R and the course content does not assume any prerequisites.


Are the courses captioned?

Yes! All videos are captioned with english subtitles that meet accessibility standards.


What if I really cannot afford this course?

Our mission is to make this course as accessible as possible to every student that wants to take it. I’ve created a scholarship program where you can submit a short application to receive the help you need for this course. Just go to the link in the main description above.

This course is closed for enrollment.

"Luka has a knack for finding the most understandable and innovative ways of breaking down and explaining processes. Luka undoubtedly made my relationship with R and statistical analysis less complicated!"
Esme, Biologist and Research Assistant