Syllabus

Table of contents

  1. Technology
    1. Edstem
    2. Gradescope
    3. bCourses
  2. Participation and Attendance
  3. Exams
  4. Materials
    1. Discussions
    2. Homeworks
    3. Lectures
  5. Disabled Students’ Program (DSP)
  6. Academic Integrity
    1. Cheating
    2. Collaboration
    3. AI policy
    4. External learning materials
  7. Grading

IMPORTANT(2026-01-09) This is a WORK IN PROGRESS, and not finalized.

Technology

Edstem

We will use Edstem as the primary means of communication for the course. This includes: Q&A forum, and official announcements.

Enrollment in Ed is mandatory. It is your responsibility to regularly check Ed for important announcements. Failure to do so may result in severe consequences for your ability to succeed in this course.

If you have questions about anything related to the course, please post them on Ed rather than emailing the instructor or TAs. Please do not post anything resembling a solution to a homework problem before it’s due. If in doubt, you should make your post private (visible to instructors only). We always welcome any feedback on what we could be doing better.

To join the class Ed: after you have officially enrolled in the course and are added to the bCourses, you will be automatically added to the course Ed. If you are not able to access the Ed, please email the course instructors.

Tip: the best (and fastest!) way to get help is to ask a question on Edstem. Please do not directly email course staff to get help. You are welcome to ask questions about nearly anything, including: assignments, course concepts, tangentially-related topics, applications to academia/industry, etc.

Gradescope

All homework will be submitted through Gradescope, and all grades will be returned through Gradescope.

To join the class Gradescope: after you have officially enrolled in the course and are added to the bCourses, you will be automatically added to the course Gradescope. If you are not able to access the Gradescope, please email the course instructors, or create a private question on Edstem.

bCourses

Lecture videos will be available from the bCourses site, under the “Media Gallery” section. We will not use bCourses for any other content.

Participation and Attendance

Attendance for lectures/discussions will not be tracked, nor part of your grade. With that said, we encourage you to attend as much of the course in-person as possible (including attending the Zoom lectures “live”), as we believe consistent active engagement leads to positive outcomes in terms of learning and course grades.

Edstem participation: Students that are particularly active (in a noteworthy, productive manner) in the course (eg Edstem, lecture, discussion) will be granted extra credit points.

Exams

There will be one midterm, and a final exam. Both exams will be on campus, in-person, paper and pencil, and proctored by course staff. No electronic devices will be allowed, including: calculators, smart phones, laptops.

For the midterm, you are allowed one page (double sided) of notes. For the final exam, you are allowed two pages (double sided) of notes.

The midterm exam date will be: Tuesday March 10th 2026, 7:00 PM (PST) (note: exam duration not yet finalized).

The final exam date will be: Thursday May 14th 2026, 11:30 AM (PST) (note: exam duration not yet finalized).

Alternate Exams: We will grant alternate midterm and final exam times for only for extenuating circumstances. If you are unable to attend the above midterm/final exam times, please contact course staff ASAP so that we can figure out an alternate solution.

Materials

Discussions

The intent for discussion is to go over course concepts in greater detail than covered in lecture, while having the benefit of small group learning headed by your discussion TA. This is a valuable opportunity to learn not only from your TA’s, but also from your peers.

You may attend whichever, as many, and as few discussion sections you like. Attendance is not tracked, nor part of your grade.

Homeworks

There will be several homework assignments for this class. You will submit your assignments on Gradescope. Grades will be released on Gradescope.

Doing the homeworks is vital for your learning. You are expected to show your work and justify all of your answers.

Homework and projects will be graded by correctness, typically via Gradescope autograder. There will be unlimited autograder attempts allowed.

Late policy: late submissions will not be accepted. After the assignment deadline has passed, if a student had not yet submitted anything to Gradescope, the student will receive 0 points for the assignment.

Extenuating circumstances: we understand that unexpected things can come up that can interfere with your coursework. If you feel strongly that circumstances outside of your control are preventing you from submitting coursework on time, please contact course staff ASAP to request an extension. If it involves sensitive data, feel free to directly email the instructor. Otherwise, create a private Ed post and we will assist you from there.

Lectures

The intent for lectures is to “steer” the course by introducing course concepts, drilling down into important concepts, and more broadly supporting student learning.

Lecture slides (pdfs) and recordings will be published to the students for later viewing.

Lecture attendance is not tracked nor part of your grade.

Disabled Students’ Program (DSP)

This course will honor student accommodations granted by the Disabled Students’ Program (DSP).

If you are a student enrolled in the DSP program and believe that your accommodations are not being met, please contact course staff ASAP (eg either a private Ed post, or an email to the instructor).

Academic Integrity

Cheating

Ethical behavior is an important part of being an engineer. It is a part of our responsibility to act ethically and honestly, and moreover, ethical behavior is what helps you learn best. Cheating is fundamentally dishonest and antisocial behavior. We have a zero-tolerance policy for cheating. Any unconfessed offense will result in negative points for the category that the offense occurs in, with no bound on how negative it can go, and a referral to the Center for Student Conduct.

You are not permitted to upload any of our problems, solutions, or your own solutions to our problems to any site that is accessible by other people. Use Ed to discuss content. The only limited exceptions to this are online communication mediums between you and the collaborating individuals explicitly listed on your homework assignment. Looking at online solutions from previous semesters or other students is forbidden, as is sharing of your solutions with others. Furthermore, students all have an affirmative duty to report possible cases of cheating or unauthorized communication to the course staff, immediately. Acknowledgement of and failure to report cheating implicates the bystander since this is academic misconduct. Cheating hurts us all and engineering ethics requires us to point out wrongdoing when we are aware of it.

Collaboration

You are encouraged to collaborate on homeworks with others; however, this collaboration must be limited to high-level discussion. All coding must be done on your own, and you should not discuss specific solutions or look at another’s code. Similarly, you may use books or online resources to help solve homework problems, but you must always credit all such sources and you must never copy material verbatim. You must explicitly acknowledge everyone whom you have worked with or who has given you any significant ideas about the homework.

AI policy

In 2026, AI in the classroom (especially “Generative AI”) takes on many forms, including: coding assistants, personalized tutors, highly effective search engines, etc.

In this course: we permit the usage of AI for purposes of learning and understanding, including:

  • Asking an LLM to explain a course concept
  • Asking an LLM to explain why a particular coding implementation works
  • etc.

In this course, we do not permit the usage of AI for generating anything you turn in, including:

  • Asking an AI to directly generate code to use in your assignments
  • Asking an AI to answer a homework/exam question
  • etc.

A good litmus test is: if you were being tutored by a course staff member (say, a TA), would you be able to ask the TA to do what you’d ask the AI to do?

Regarding coding assistants: although I understand the temptation to utilize coding assistants for coursework, I do feel strongly that one should first develop a strong foundation in Python/numpy/pytorch coding abilities before using coding assistants.

Any violations of the “AI policy” will be treated as an Academic Integrity violation, with appropriate consequences.

External learning materials

As of 2026, there are many helpful resources easily accessible on the internet (eg YouTube, blog posts, other course materials) that are relevant to this course’s material.

Our policy on this is: we allow (and encourage!) learning course material from external resources. There’s a lot of great stuff out there (many of which the instructors used themselves to create this course!).

What you may not do, however, is pass off external resources as your own work. For example, you may NOT do the following:

  • Copy and paste code from a blog post to your homework solution
  • Copy a mathematical derivation from the internet to pass of as your own work

If you feel that your submitted work was considerably influenced (or “inspired”) by learning from an external influence (but, that the submitted work is still your own!), please cite the external resource in your submission.

Grading

(2026-01-11: grade breakdown not yet finalized)

The grading breakdown is as follows:

  • Homework: 40%
  • Midterm Exam: 20%
  • Final Exam: 40%

Attendance will not be graded or tracked for lectures/discussions.

Final course grades will be subject to a curve to meet university and departmental guidelines.

Incompletes: I highly recommend students to NOT rely on Incomplete grades being granted for this course. As this course is not a regularly offered course (as opposed to, say, Data C88C), it’s highly unlikely that we will grant any Incomplete grades for this course.