Overview: Probability is everywhere in computer science. In networks and systems, it is a key tool that allows us to predict performance, to understand how delay changes with the system parameters, and more. In algorithm, randomization is used to design faster and simpler algorithms than their deterministic counterparts. In machine learning, probability is central to the underlying theory. This course provides an introduction to probability with a focus on computer science applications. We will discuss elementary probability theory, including topics such as discrete and continuous random variables and distributions and Markov chains, and settings in which these are used in computer science (e.g., modeling real-world workload distributions, analyzing computer system performance, and designing and analyzing randomized algorithms).
Deadlines, late days, and extensions: Homework must be submitted by the day and time at which it is due. You may take 5 late days during the semester. These can be used for any reason, without penalty, and you do not need to ask me or tell me that you are using them. Details:
I will grant additional extensions only if I hear from your class dean that you are facing extenuating medical or personal circumstances.
2. Projects (40%). There will be three projects throughout the semester. The first will be before spring break and the second and third will be after spring break. The third project is a "final project" that will be due during exam period and will be in place of a final exam.
3. Midterm exams (20% and 25%). There will be two in-class midterm exams, the first in early March and the second in mid April. The first midterm will be worth 20% of your grade, and the second midterm will be worth 25% of your grade.
I will not take attendance, but I strongly encourage you to attend all class meetings. You likely will find it difficult to keep up with the material if you do not come to class, and I will not use office hours time to teach you material from lectures that you decided to skip.
If you discuss an assignment with other students in the class, please note their names in a comment at the top of your submission. You do not need to note if you consulted with me or the course TAs. Do not discuss assignments with anyone other than myself, the course TAs, and students currently enrolled in the class, and do not look for solutions on the internet.
Exams must be completed individually, without the help of notes, textbooks, the internet, or other people.
If you are unsure whether something constitutes academic dishonesty, please ask me. There's absolutely no penalty for coming to talk to me about whether a certain form of collaboration is allowed.
If you have a documented disability that requires accommodations, you will need to contact Accessibility Services (accessibility@amherst.edu or 413-542-2337). After you have arranged your accommodations with Accessibility Services, please set up a time to meet with me to discuss how we can best implement your accommodations in this class.