Course Meetings

Classes are held twice a week and involve a mixture of lecture and active participation, including back-of-the-envelope estimations, derivations, and natural philosophy. The course is intended to serve as an introduction to the overarching principles of modern biological inquiry, with special attention to how they relate to physics, chemistry, mathematics, engineering, and computer science.

Recitations are held once a week. These sessions are led by pairs of graduate and/or undergraduate TAs, and are designed to help guide your thinking on problem sets, and further explore topics introduced in class. Feel free to attend whichever section is most convenient, within room capacity limits.

Tutorials are also held once a week, hosted by the head TAs. These supplementary sessions are designed to be exploratory extensions of each week’s content. Examples include a crash course in programming with Python and a live microbiology experiment.


Regular attendance is an expectation for all students in the class. As a general rule, “on time” means that you are sitting in the classroom five minutes early. You may use electronic devices (e.g. tablet, laptop) in class for taking notes, but please don’t let them become a distraction.


There will be no exams, quizzes, reports, or research proposals; your final grade is based entirely on homework. Homework is assigned on Thursdays and is due the following Thursday at 11:59 pm. Late homework submissions (submitted after 11:59 pm on the date due) will incur a modest penalty. For each day an assignment is late, 10% will be deducted from the maximum possible score, beginning immediately after the deadline. For example, if your submission is handed in at 1:00 am on the Friday after it is due, your new maximum possible score is 90%; any points you earned beyond this value will no longer count. A submission received four days late will maximally earn 50%. The goal is to encourage timely submissions — which keeps the turnaround on grading quick for everyone — while acknowledging that many people have busy schedules.

In addition, we will automatically drop your lowest-scoring set when calculating your final grade.

Absences, Extensions, and Ditch Day

Homework extensions may be granted in extenuating circumstances, and preferably with as much advance notice as possible. Last-minute requests (or requests after the deadline) will generally not be granted. To request an extension, email Kian with the subject line [Homework #] Extension Request.

In the event that Ditch Day falls on the day that an assignment is due, the deadline will be extended by two calendar days (i.e., if Ditch Day is on a Thursday when a problem set is due, then the revised due date will be Saturday at 12:00 pm). Any course meetings affected by Ditch Day will be rescheduled and posted on the homepage.

Homework Submissions

All homework will be submitted to Gradescope. To ensure proper grading, homework must be submitted in adherence to the following conventions:

  • For text solutions, submit a single PDF with the filename lastname_firstname_hw#.pdf. This can be scanned handwritten work, but LaTeX is preferred. Assign the pages corresponding to each problem using Gradescope’s UI when you do so.
  • Similarly, for code solutions, submit a completed, fully-executed Colab template notebook with the filename lastname_firstname_hw#.ipynb to Gradescope. Details on how to work with Colab (including guidelines for code submissions) can be found on the tutorials page.

Any submission that does not completely adhere to these requirements will not be graded.

Homework Regrades

We do our best to grade homework as transparently and accurately as possible, but we’re only human; if you feel we’ve made a mistake with your submission, you may request a regrade. To do so, please use Gradescope’s built-in regrade feature, and explain the reason for your request in the body of the message.

The regrade window for an assignment opens when grades are published and closes one week later. Regrade decisions are final.

Collaboration Policy and the Honor Code

You are expected to follow the Caltech Honor Code at all times. As a reminder, this states:

No member of the Caltech community shall take unfair advantage of any other member of the Caltech community.

Collaboration is imperative to scientific discovery. You are encouraged to work together on homework assignments, but all work handed in must be your own. This means that you may not hand in work copy-pasted from those you worked with.

You may use resources on the internet, primary literature, or textbooks to help you answer questions, although you must provide a reference. You may not refer to homework questions or solutions from previous editions of this course or others like it.

Programming Assignments

For programming, please follow the 50-foot rule from CS 11:

[...] If you help another student with their programming problems (including debugging), you must not consult your own code while doing so. Specifically, we ask that your own code be at least 50 feet away i.e. not visible to you or the person you are helping while you are helping them. This means that you may work with each other on programming problems but you may not copy others code directly. [...] Help them with your brain, not with your code.

We have designed the tutorials to provide you with all of the information you need to complete the coding problems in the homework. While you may use any of the code provided in the tutorials to solve your homework, please do not just copy-paste it directly into your notebook. This is a good way to learn absolutely nothing. Instead, type it out by hand and ensure you understand what each line actually does.

Generative AI Policy

You may not use generative AI tools (e.g. ChatGPT, Copilot, Colab’s built-in AI) in this course. This is not to deny the increasingly important role that LLMs play in the modern practice of programming and research; we merely note that, in an instructional capacity in an introductory course, we generally find them counterproductive.

The lone exception is that, on rare occasions, we may explicitly ask you to engage with AI tools on a per-problem basis. These cases will be clearly marked on the respective homework sets.


You may contact the TAs via email at any time, but please don’t be spammy or rude. TAs are generally not expected to reply to emails outside of normal hours, although each TA has their own preferences. Remember that you are reaching out to another human!