Data 100

Frequently Asked Questions for Spring 2022 Data 100

[UPDATE 1/18/22] Data 100 will be online for at least the first two weeks of the semester.

See more details on the course website. Please make sure you are subscribed to the EdStem discussion forum for latest updates as we prepare for this semester. If you cannot access Ed at this time, please join using this signup link.

Q. Will Data 100 be taught in hybrid mode for the Spring 2022 semester?

A. Yes.

  • Lectures will be available in three formats: Live attendance, Zoom simulcast of the live lecture, and a recording of the live lecture posted within 24 hours.
  • There will be both in-person and online options for discussions, labs and office hours. Most options will be in-person.
  • There will be two midterms and a final exam. There will be online options for all exams.
  • The above means that time conflicts should not be an issue for anyone.

Q. Where is the course website?

A. Here.

Q. What are the official prerequisites for this course?

A. The official list of prerequisites is:

  • Data 8.

  • CS 61A or CS88 or Engineering 7. We strongly recommend either CS 61A or CS 88.

  • EE 16A or Math 54 or Stat 89A. This may be satisfied concurrently with Data 100, but we strongly recommend that you finish a linear algebra course before taking Data 100.

Q. Will the official prerequisites be enforced?

A. The official prerequisites are being strictly enforced by CDSS. Decisions on any requests for exceptions to this policy are being made by the CDSS advisors. To request an exception see https://data.berkeley.edu/academics/data-science-undergraduate-studies/courses/spring-2022-classes - do not email instructors about this as we are not making these decisions at all.

Q. I am a graduate student but the system won’t let me enroll in Data 100 due to missing prerequsites, what can I do?

A. Graduate students should use the C200 class code, not C100: C200 has a proper graduate code so you don’t have undergraduate prerequisite issues. There will be some differences in grading and homework, but the main content is the same.

Q. I am waitlisted, what should I do? What are my chances of getting into this class?

A. Currently (Jan 14, 2022) the waitlists for Data C100/C200 are relatively short compared to the overall class size, so we do not expect any issues allowing waitlisted students once the usual early-semester shuffle takes place.

We recommend that you sign up for the class EdStem and follow the class assuming you’ll have a slot soon. All lectures and class materials are openly available on the class website and all discussions happen on EdStem. We’ll be monitoring the waitlist and will do our best to ensure all waitlisted students can enroll.

There is no material on bCourses that you need or will miss, and if/when you get formally enrolled, you’ll be automatically added to bCourses for grade management (the only thing we keep there, to sync with Gradescope). In the meantime, you can join Gradescope using this code: 74WGNK.

Q. I have a Concurrent Enrollment Request that hasn’t been approved yet, what should I do? What are my chances of getting into this class?

A. By campus policy, we must first process the waitlist in its entirety before we can admit you. We will do all we can to ensure all waitlisted students are promptly admitted, so that you can also enroll in the course, though we can not provide 100% guarantee that will be the case. But given we think it is likely we’ll be able to admit you, we strongly suggest you start working on the course, following lectures and turning in assignments, from the start. This will prevent you from falling behind and will give you the best chance of success in the class. Zoom links are only available to registered Berkeley students, though we plan to publish lecture recordings within a day of the live session for asynchronous viewing.

Q. I am a campus student and would like to audit the course, what can I do?

A. Most class materials are available online to all campus students, and you can access the lecture videos, slides, etc. without limit, as well as use the online Data 100 DataHub (our JupyterHub instance for this class).

Note however that the class EdStem, our only other class resource, is reserved for enrolled students and faculty auditors, as homework details and solutions are discussed in that environment.

Q. What is the proctoring policy for exams?

A. We will offer in-person and online exams, to be taken synchronously .The online exam will be proctored with a minimally-invasive Zoom setup that has been used successfully on campus for other courses and that does not require you to install any custom proctoring spyware on your computer. The in-person exam locations (DSP or not) will have regular proctoring.

Q. What is the alternate exam policy?

A. TBD, but we will be offering alternate exams for both midterms and the final exam.

Q. When will the full schedule of labs and discussions be announced?

A. The schedule (which is always subject to change) is located on the course homepage.

Q. Where can I find links to the class schedule, optional textbook, and other additional relevant resources?

A. Check out the course homepage and the resources page. Don’t hesitate to make suggestions by filing an issue on the class repository (or even better, propose a new pull request with your additions!).

Q. Where is the Class EdStem?

A. Here. If that link doesn’t work, here is the signup link. If your question isn’t answered in this FAQ, please try EdStem next before emailing the instructors.

Q. I can’t find any information on bCourses, why?

A. We will only be using bCourses for synchronizing access to Gradescope. As long as you are enrolled in the class right now, you don’t need anything. All class materials are available online through the website; communications happen on EdStem; and computational work is done on the DataHub.

Q. I have added the course later in the semester. Can I catch up? Can I be excused for all late work

A. The answer to the first question is impossible to give in general, as it depends both on how late you add the course, and what your own background is. But as a general rule, the course moves quite quickly and covers new ground from the start. We estimate most students will probably struggle to catch up effectively if they join any later than the first few days of the semester, unless they have a particularly strong background already in the initial topics (probability, SQL, Python and Pandas).

As for the second part of this question - in fairness to our desire to apply our policies as uniformly and universally as possible, we do not make separate considerations for late work based on the date you joined the course. We offer fairly generous drop/late assignment policies which you can take advantage of and apply them to early work, but there are no extra allowances based on your start date.

To get a section (discussion and lab) assignment, please contact Kanu Grover.

Q. I didn’t turn in a Lab/HW/etc in time, can I have an extension?

A. We have a generous drop policy for assignments and late policy for projects; therefore we do not provide extensions, unless there is a major and documented set of exceptional circumstances (death in the family, outage in the hub that prevents students from working, natural disaster, …). If the problem is class-wide we’ll make announcements on EdStem, else you can request the extension by contacting our Communications TA, Samantha Hing. For more details, see our syllabus.

Q. I would like to make a class-wide announcement about my project/group/initiative/etc.

A. We only allow posts made on EdStem and you must make it yourself, we do not make posts on your behalf. These are our guidelines for EdStem posts from student groups - they must be text-only posts (no videos) where the announcement:

  1. Has to do with teaching or tutoring in a non-commercial setting, or
  2. is directly related to the material in the course, or
  3. is seeking to recruit students to help with the public good in a non-financial way (no solicitations for donations!), and in a context explicitly connected to their work in the course.

Q. Who do I contact if I have further questions? How do I email the instruction team?

A. Please e-mail data100.instructors@berkeley.edu and one of the instructors will get back to you. Note that to ensure more timely responses, this address is monitored by the team of the two lead instructors (Josh Hug and Lisa Yan) the Head TA (Andrew Lenz), as well as several lead GSIs, to ensure more timely responses. You can contact Josh and Lisa directly for matters that require strict privacy and their direct attention.

We’re excited to have you in the class this Spring!

Lisa, Josh, and the rest of your Spring 2022 instructional team.