CMSC 27100 — Syllabus

Welcome to CMSC 27100! This document discusses course logistics. You should read this carefully at least once, directing careful attention to the lengthy section on collaboration and academic integrity.

For a general introduction to the course content, you can check out the course introduction.

General information

Instructor: Jonathan Liu (jonliu@uchicago.edu)
Office hours: TBA
Graders: Surya Chinnappa; Pratyush Kalli
Lecture: Tuesdays and Thursdays, 6:00-8:30pm at Ryerson Physics Lab 251

Communication

We will use Canvas, Ed Discussion, and Gradescope. The pages specific to this course are linked below.

Ed Discussion: This is the primary place for discussion in this course. We will use it for general course communication, and we encourage you to ask any and all questions here on Ed. We especially hope that you direct questions about the problem set, lecture topics, or logistics here. Feel free to ask for help or hints as needed. However, for any sensitive communications that you do not wish other students or graders to see, you are free to email me.
Gradescope: We will use Gradescope for problem set submissions and for returning graded papers. We will also use Gradescope to facilitate regrade requests.
Canvas: Non-public materials (e.g. problem sets and solutions) will be posted on Canvas.

Written Resources

You are not required to purchase a textbook for this course. All problem sets will be self-contained. I will post notes near each lecture, which will serve as an official record of the topics covered.

Many of the notes for this class were created from notes written by Timothy Ng and extended by Robert Rand and David Cash.

While the course notes posted will be sufficient for this course, it can be helpful to see content explained in a different way and to have more practice problems and examples than can be covered in class. For this reason, I recommend you get access to a copy of the following resources. You should be able to do so for free online - ways to do so are attached to each individual resource. Readings from these resources will be posted to the course schedule. Specific exercises from these books will also be recommended.

Discrete Mathematics and Its Applications. by Kenneth H. Rosen.: The most comprehensive resource for this course. Other editions are also fine, but be careful to check that the content aligns. This text has many exercises. It can be accessed at the UChicago library online.
Introduction to Probability, 2nd ed. by Joseph K. Blitzstein and Jessica Hwang: In Unit 2 of our course, we cover Chapter 1 of this book, and touch on topics from Chapters 2-4 but in less detail than this book does. It'll be good as a resource, but note that it also deals with continuous probability whereas we stick to discrete situations.

Other Resources

Outside of lecture, the lecture notes, and the textbooks above, there are a couple of other resources to help you succeed in this course.

Office Hours: I will host weekly office hours. Office hours are a mix of one-on-one and group interaction. They sometimes become a de-facto one-hour study group. You are welcome to come and ask for hints (e.g. "Where do I even start?"), ask for feedback on your progress (e.g. "Is this type of solution on acceptable?"), or to talk about the course material and logistics in general. You may come alone or with peers in the class, and are encouraged to work with your classmates at office hours. It can be a good place to work on the homework, with an instructor right there whenever you have a question or run into an issue. That said, office hours generally aren't the best time to be seeing the problems for the first time - instructor help is much more beneficial to you if you've spent some time thinking about the problem on your own first! If you can't make the posted office hours, send me an email and we will find another time to meet!
Ed Discussion: You can also get help on Ed Discussion. As mentioned above, it will be used for us to make announcements, but will also function as an asynchronous office hours. Just like office hours, you can and should ask for hints, ask for feedback on your progress, or ask about course material and logistics. You should also feel free to answer questions that other students ask! However, please do not post any solutions to HW problems publicly on Ed. If you would like course staff to check your solution, feel free to make a private post!

Assigned Tasks and Policies

Your work this quarter will consist of attending lecture, doing readings, and submitting assignments. Assignments will consist of problem sets and three unit exams.

Problem sets

Problem sets are a chance for you to practice the skills you've learned in class and get feedback on that practice. They will also sometimes ask you to read and learn from online resources. They will be assigned Tuesdays after lecture and are due the following Monday night at midnight Central Time. Weeks with unit exams will have lighter homework assignments, giving you more time to study for the exam and work on resubmissions.

Resubmissions Because problem sets are a chance for you to learn and practice, you will be allowed to resubmit each problem set. You may resubmit as many times as you would like up until the corresponding unit exam, but they may take a few days to be graded so it would be prudent to resubmit early. For any question you would like to resubmit, the resubmission must contain the following:

Your original answer to the question.
A description, in your own words (don't just copy what the grader wrote!), of what was incorrect about the original answer, and why that occurred. Was it a misunderstanding of a term or concept, or perhaps just a calculation error? Your honesty is appreciated here, both to help yourself learn and to help me understand if there's anything I can do better.
Your updated answer to the question. Any substantial change to your original answer should be justified by your description above.

To receive full points on a resubmitted assignment, your resubmission must both have an accurate updated answer and an accurate reflection (i.e. did you correctly identify what was incorrect?). It must also describe why you made the error, but the reason will not be evaluated (i.e. you didn't need to have a "good" reason to get it wrong the first time).

Unit exams

Each unit of this course will end with a Unit exam. Exams will be in-class with no outside aid (no textbooks, cheat sheets, devices, etc.). Content-wise, they will focus heavily on the current unit, but proof/reasoning skills and ideas from earlier units may show up on a later exam. They will focus on concepts and skills, and will require very little memorization (i.e. relevant theorems and definitions will mostly be provided). More details will be released as the exams approach.

Course Participation

Your active engagement in this course, both with me and with your peers, are important to your success learning the material. Up to 5% of each unit exam grade may be replaced (e.g. an 85% can become a 90%) by course participation during that unit. Course participation can take the form of

attending lecture,
asking or answering a question on Ed,
attending office hours,

each of which will contribute 1% per occurrence within the unit.

Meet the Professor

You must sign up for a 10-minute meeting with the professor in the first two weeks of the course. A sign-up sheet will be available on Canvas. These may be on Zoom or on campus. This is for me to get to know you and vice versa - no need to prepare or study for it, though you can prepare questions to ask me.

Accessibility

Students with disabilities who have been approved for the use of academic accommodations by Student Disability Services (SDS) and need reasonable accommodation to participate fully in this course should follow the procedures established by SDS for using accommodations. Timely notifications are required in order to ensure that your accommodations can be implemented. Please meet with me to discuss your access needs in this class after you have completed the SDS procedures for requesting accommodations.

Academic Integrity: Collaboration, LLMs, and other resources

It is your responsibility to be familiar with the University’s policy on academic honesty and plagiarism. Instances of academic dishonesty will be referred to the Office of the Provost for adjudication.

Can I work on homework with other people in the class?

Please do! Working in groups is a great way to share resources, keep each other on track, and develop an overall support system. Learning to productively work in groups by articulating your ideas and processing others' is incredibly valuable as well. However, all submitted solutions should be entirely written by you alone. You should never read the solutions your collaborators intend to submit, or even drafts of those solutions. You must include a list of your collaborators in your submission. Also, make sure to be aware of your individual capabilities. Working productively in groups is an incredibly important skill, but remember that the primary skills that we are trying to develop in this course (and the skills that you'll have to individually demonstrate on exams) are problem-solving and logical reasoning. If you're worried that you're getting carried along by your study group, I'd recommend working on some sample non-homework problems on your own for a low-stakes gauge of your abilities. Of course, these non-homework problems and their solutions can also be discussed freely at office hours or on Ed!

Can I use an LLM?

You should view an LLM as a readily accessible but sometimes untrustworthy TA. In practice, this means:

DO: Ask it to re-explain a topic you didn't understand from class.
DO: Ask it to generate a practice problem or quiz for you.
DO: Ask to explain a topic to it to see whether you fully understand it.
DO: Ask it to write out a solution for a non-graded problem, for example one from a textbook. Though, of course, it will be more beneficial if you try to solve it yourself first!
IFFY: Ask it to check your solution. You can do this, but you can also just make a private post on Ed asking course staff to check your work - we are happy to do that too, and will likely be more accurate - see below.
DO NOT: Ask it for solutions to homework problems (unless given permission).
DO NOT: Blindly trust its output. LLMs are, by construction, a next-word predictor trained on the internet, so they are well-equipped to write human-sounding and logical-sounding text. Of course, humans can be convincing even when they're wrong, so in our class logical-sounding is not good enough.
DO NOT: Assume that anything it discusses is fair game. Solutions that use different theorems/tools or different definitions for terms than the ones discussed in class may not be accepted.

What about the internet?

Basically the same response - it's a great place to get alternate explanations to topics or to find practice problems, but you should not look for solutions to homework problems and you should not trust that it is always either accurate or acceptable for this course.

I accidentally found a solution to a problem online or in a textbook (or maybe just a big hint). What should I do?

Just let me know via a private post to Ed, and we'll sort it out. You will not be accused of academic dishonesty.

Evaluation

Your final grade is based on the following graded components:

7 problem sets, worth 21% in total,
Three unit exams, worth 35%/25%/15% (in order of your performance), buffered by course participation,
Meet the Professor, worth 4%.

Test statistics will not be released. Because the course is relatively small, your grade will not depend on the performance of your peers.