Welcome to DSC 206 in Winter 2026! This page should answer most of the questions you might have about how the course is run.
Due to instructor traveling, there will be no class on Jan 5, 2026. However, there will be a make-up first class on Jan 8, Thu, at 5 pm, at the Atkinson Bldg, 4th Floor, EnCORE Institute seminar space. Hope to see most, if not all, of you there.
This term of DSC 206 AFDS is taught by Prof. Arya Mazumdar
email: arya@ucsd.edu
This term the TA for DSC 206 AFDS is
Xiaxin Li <xil095@ucsd.edu>
Class Location: FAH 1101
Time: Mon 5:00 PM - 7:50 PM
The lecture slides and/or any notes will also be posted on the lectures page below.
To get started in DSC 206 AFDS, you'll need to set up accounts on a couple of websites.
We'll be using Campuswire as our course message board. Campuswire is like Piazza, but unlike Piazza, Campuswire does not sell student data to third parties. You should have received an invitation via email, but if not you should get in touch with a course staff member as soon as possible, as we'll be making all course announcements via Campuswire.
If you have a question about anything to do with the course — if you're stuck on a homework problem, want clarification on the logistics, or just have a general question about data science — you can make a post on Campuswire. We only ask that if your question includes some or all of an answer, please make your post private so that others cannot see it. You can also post anonymously if you would prefer.
Course staff will regularly check Campuswire and try to answer any questions that you have. You're also encouraged to answer a question asked by another student if you feel that you know the answer.
We'll be using Gradescope for homework submission and grading. You should have received an email invitation for Gradescope, but if not please let us know as soon as possible (preferably via Campuswire).
Some aspects of the course, like office hours and the remote discussion, will be held using Zoom. You should already have an account through UCSD; see the Zoom guide for more help. Note that you will not be expected to have a webcam!
We'll use Canvas for the course gradebook and some announcements.
No materials are required for this course, as well as our own course notes. That said, here are some books that you might find useful.
Mainly the following book will be followed.
Avrim Blum, John Hopcroft, and Ravindran Kannan: Foundations of Data Science. Link.
We will also refer to the following book.
Jure Leskovec, Anand Rajaraman, Jeff Ullman: Mining of Massive Datasets. Link.
Both the books are available freely, follow the links.
The Instructors and TA/Graders will be available to answer your questions every week. All times below are PDT.
TA's office hours: Thursdays 2-3pm, or by appointment.
Location: https://ucsd.zoom.us/j/5465321979
Homeworks will be distributed evenly throughout the term.
HW1 out Jan 13 due Jan 20
HW2 out Feb 10 due Feb 17
HW3 out Mar 10 due Mar 12 (Mandatory Homework to satisfy the Core Course Requirement for MS and PhD DS students. Others may skip, unless they want to substitute either HW1 or HW2 scores with this HW).
Due to the accommodation above, late homeworks will not be accepted under any circumstances.
There will be two midterm exams. No final. The exams will be an hour long each, and will be at the beginning or end half of the class.
Midterm 1: Feb 2 in class.
Midterm 2: Mar 2 in class.
The final grading will be done based on the following breakdown of contribution.
Homework: 50%
Exam 1: 25%
Exam 2: 25%