EE BIOL C177/C234

Practical Computing for Evolutionary Biologists and Ecologists

Author

Chuliang Song

Published

October 22, 2026

Welcome

Welcome to EE BIOL C177/C234: Practical Computing for Evolutionary Biologists and Ecologists—or, as I like to say, a crash course in “computational Kung-Fu”.

Previous Offerings

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Course Info

  • C177 Syllabus: Fall 2026 undergraduate syllabus (PDF).

  • Where and When: Tuesdays and Thursdays, 10:00 AM to 10:50 AM, in W.G. Young Hall CS76.

  • Office Hours: Tuesdays, 3:30 PM to 4:30 PM, in Botany Building 210H.

  • The Grind: Yes, there will be weekly assignments (non-graded), 2 PSETs, and 1 final project. If you want to build computational muscle, you’re going to have to sweat a bit.

  • Assignments: All due Sundays at 11:59 PM Pacific Time.

    Assignment Released Due
    PSet 1 Tuesday, October 13, 2026 Sunday, October 25, 2026
    PSet 2 Tuesday, November 3, 2026 Sunday, November 15, 2026
    Final Project Tuesday, November 17, 2026 Sunday, December 6, 2026

  • What to Bring: Just your laptop and a healthy dose of intellectual curiosity. If you have played with R before, great; if not, don’t worry—you’ll pick it up.

  • Course Material: This website. This lecture note will be updated as the course progresses.

  • If I’m losing you, boring you, talking too fast, too slow, whatever – speak up! Your feedback is my compass.

How to Use the Lecture Notes

Your left sidebar is your map to the course, showing all lectures—just a click away. On the right, you’ll see a table of contents specific to each lecture.

In this course, code examples will appear in blocks like this:

x <- 1 + 1
x^2
1
Calculate 1 + 1 and assign it to the variable x.
2
Calculate the square of x.

See the little circle on the right? Hover over it for a quick explanation of the code. When you hover over the code block itself, you’ll also spot a “copy” button—perfect for copying and pasting it into your R console to try it out yourself (fun fact: that’s how a large portion of coding is done in real life).

To show stepped progress, we’ll often add to existing code blocks. New additions are highlighted for clarity. For example:

x <- 1 + 1 
x^2 
x^3
1
Calculate the cube of x.

You’ll find key computational tools and R packages highlighted in purple (e.g., GitHub and ggplot2). R functions are indicated in red and always include parentheses, such as sum().

Throughout the course, expect tips, tricks, and even a few fun facts sprinkled in. While not essential, these extras might give you an edge or deeper insight. Some of them are collapsible, so you can click to expand and explore them at your own pace. Look out for these in green boxes, like this:

As advertised, this is a tips box.

I have included many exercises throughout the notes. These are your chance to practice what you’ve learned. Just fill in the blanks (__) with the correct answer and then run the code block to check your work. If you ever get stuck, the Solution is just next to it. For example,