Syllabus

Syllabus#

Course description#

Application of machine learning tools, with an emphasis on solving practical problems. Data cleaning, feature extraction, supervised and unsupervised machine learning, reproducible workflows, and communicating results.

Class meetings#

Lectures:

Section

Day

Time

Location

CPSC 330 101

Tue/Thu

3:30 - 4:50 PM

SWNG-Floor 2-Room 222

CPSC 330 102

Tue/Thu

11:00 AM - 12:20 PM

SWNG-Floor 2-Room 222

CPSC 330 103

Tue/Thu

5:00 - 6:20 PM

SWNG-Floor 2-Room 222

Tutorials:

Section

Day

Time

Location

CPSC 330 T1A

Friday

9:00 - 10:00 AM

DMP-Floor 2-Room 201

CPSC 330 T1B

Friday

11:00 AM - 12:00 PM

DMP-Floor 1-Room 101

CPSC 330 T1C

Friday

2:00 - 3:00 PM

MCLD-Floor 3-Room 3002

CPSC 330 T1D

Friday

3:00 - 4:00 PM

DMP-Floor 1-Room 101

CPSC 330 T1E

Thursday

5:00 - 6:00 PM

MCML-Floor 1-Room 158

CPSC 330 T1F

Thursday

1:00 - 2:00 PM

MCLD-Floor 3-Room 3008

CPSC 330 T1G

Thursday

2:00 - 3:00 PM

ORCH-Floor 4-Room 4018

CPSC 330 T1H

Thursday

10:00 - 11:00 AM

MCLD-Floor 3-Room 3014

CPSC 330 T1J

Friday

10:00 - 11:00 AM

MCLD-Floor 3-Room 3014

CPSC 330 T1K

Friday

11:00 AM - 12:00 PM

MCLD-Floor 2-Room 2018

CPSC 330 T1L

Thursday

9:00 - 10:00 AM

ORCH-Floor 4-Room 4074

Tutorials for this course will be conducted by TAs and follow an office hours format. Attendance at tutorials is optional. However, participating will allow you to engage in more personalized discussions with TAs, providing you with valuable one-on-one time and an opportunity to deepen your understanding of machine learning concepts.

For office hours, please refer to the Calendar.

Teaching Team#

Instructors:

Course co-ordinator#

  • Devyani McLaren (cpsc330-admin@cs.ubc.ca), please reach out to Devyani for: admin questions, extensions, academic concessions etc.

TAs#

  • Akash Adhikary

  • Amirali Goodarzvand Chegini

  • Aryan Ballani

  • Atabak Eghbal

  • Derrick Cheng

  • Frederick Sunstrum

  • Hongkai Liu

  • Noah Marusenko

  • Jialin (Mike) Lu

  • Kimia Rostin

  • Mahsa Zarei

  • Mike Ju

  • Mishaal Kazmi

  • Rubia Reis Guerra

  • Shadab Shaikh

  • Sohbat Sandhu

  • Stash Currie

  • Tianyu (Niki) Duan

Registration#

Waitlists:

The general seats available in this class usually fill up very quickly. Once the general seats are taken, the only way to register for the course is to sign up for the waiting list. For questions about the waiting list policies, see here. You should sign up for the waiting list even if it is long; a lot of students tend to drop courses. Signing up for the waiting list also makes it more likely that we will open up extra sessions, expand class sizes, or offer additional courses on these topics. The instructors have no control over the situation and I cannot help you bypass the waiting list.

Prerequisites: The official prerequisites can be found here. If you do not meet the prerequisites, see here and here. We were told that students should not visit the front desk in the CS main office about prerequisite issues, because the folks at the front desk do not have the authority to resolve prerequisite issues.

In practice, the prerequisite is familiarity with Python programming.

Auditing: If the course is full, we cannot accommodate official auditors. If there is space and you would like to audit the course, please contact the instructor. All UBC students are welcome to audit the course unofficially.

Grading scheme#

The grading scheme for the course is as follows:

Component

Weight

Location

Syllabus quiz

1%

PrairieLearn

iClicker participation

5%

iClicker Cloud

Assignments

22%

Gradescope

Midterm 1

21%

PrairieLearn

Midterm 2

21%

PrairieLearn

Final

30%

PrairieLearn

iClicker#

The iClicker participation grade will mainly consider your engagement rather than the accuracy of your responses. Nevertheless, these questions are intended to facilitate your learning, so please make an earnest effort when providing your answers.

Assignments#

The plan is that most of the assignments will contribute equally towards the overall Assignments grade.

We will drop your lowest homework grade.

See this document for more detailed instructions on submitting homework assignments.

For the full policy on grades, see this document. We understand that grades are important for you for several reasons. But try not to focus too much on them. You will have a better learning experience and in general, you’ll be happier in life if you focus more on learning the material well. For the grading scheme we wish we could use this.

Late policy

Assignments will be due at 11:59 PM on the due date. If you cannot make this due date, you may use a “late token”. Each student will have 4 late tokens for the entire semester, we will track them on PrairieLearn.

For example, if assignment is due on a Monday at 11:59 pm:

  • Handing it anytime on Tuesday will cost you 1 late token (irrespective of whether it’s a holiday).

  • Handing it anytime on Wednesday will cost you 2 late tokens (irrespective of whether it’s a holiday).

There is no penalty for using “late tokens”, but you will get a mark of 0 on an assignment if you:

  • Use more than 2 late tokens on the assignment.

  • Use more than 4 late tokens across all assignments.

We will post solutions 48-hours after the due date.

Lecture recordings#

This is an in-person class, and we do not livestream or make recordings available by default. If you miss a class, you can catch up by reviewing the lecture notes and talking to your peers. Section 102 lectures (11 am to 12:20 am) are being recorded, but the recordings are not shared widely. Typically, the backs of students sitting in the first three to four rows may appear in the recording. If you prefer not to be recorded, please avoid sitting in those rows. When recordings are available, instructors may grant access to students who were absent for approved reasons only (e.g., illness, jury duty, etc.).

Use of AI in the course#

Use of AI-based content generation tools, or AI tools, is permitted for assignments and project work in CPSC 330. It is not allowed during midterms and the final exams.

Additionally, students are required to disclose any use of AI tools for each assignment. This includes

  • Referencing the tool used

  • Including any prompts used to query

  • Including the output of the prompts and a discussion of if/how you modified the result

Failure to follow this policy will be considered a violation of UBC’s academic policy.

When using AI tools for your assignments, be mindful of their impact on your learning. Consider carefully whether they are improving or hindering your learning, and make a conscious decision about their use.

Midterm#

Check the Calendar for midterm dates.

There will be two midterms in CPSC 330 and both of them will be conducted in the CBTF via self-reservation over a two-day period. The CBTF (computer based testing facility) is designed to enhance the student’s writing experience by providing them with a familiar, secure testing environment with quick access to technical support, as well as support from their instructor for common access issues.

Centre for Accessibility (CfA) Exam Accommodations#

Students who are registered with the Centre for Accessibility (CfA) with exam accommodations listed below will need to write all of their assessments in the Computer-Based Testing Facility (CBTF). The CBTF will provide the following accommodations:

  • Extended-time (up to 4x)

  • Distraction-reduced environment

  • Close proximity to washroom

  • Phone permitted for medical purposes

  • Medical equipment/supplies/food

If you have an accommodation that is not listed above, you will write your assessments with the CfA and will need to book a time by their deadline. Please do not book any assessments with the CfA if you are expected to write in the CBTF, as the CfA will cancel the exam booking and ask you to book it yourself with the CBTF. If you have any concerns about your accommodations being met in the CBTF, please reach out to your Accessibility Advisor.

For more information, please see the CBTF page.

Final exam#

The final exam is scheduled for the exam period and is likely to be comprehensive, covering the material taught over the course of the semester.

Academic concessions#

UBC has a policy on academic concession for cases in which a student may be unable to complete coursework. According to this policy, grounds for academic concession can be illness, conflicting responsibilities, or compassionate grounds. Examples of compassionate grounds, from the above policy, include “a traumatic event experienced by the student, a family member, or a close friend; an act of sexual assault or other sexual misconduct experienced by the student, a family member, or a close friend; a death in the family or of a close friend.” To request an academic concession, please write to the course coordinator (cpsc330-admin@cs.ubc.ca), with your section instructor copied in the email. Additional documentation might be requested. We will review your situation and determine whether to approve the concession, and if approved, the appropriate steps to follow.

Code of conduct#

  • If you plan to engage in non-course-related activity in lecture (Facebook, YouTube, chatting with friends, etc), please sit in the last two rows of the room to avoid distracting your classmates.

  • Do not distribute any course materials (slides, homework assignments, solutions, notes, etc.) without permission.

  • Do not photograph or record lectures (audio or video) without permission.

  • If you commit to working with a partner on an assignment, do your fair share of the work.

  • If you have a problem or complaint, let the instructor(s) know immediately. Maybe we can fix it!

  • During the exam period, do not disclose, discuss, or share any part of the exam with any other individual, except as directly permitted or required by the course instructors. This includes discussion in person, online, or through any electronic means. Violation of this will result in academic penalties, which may include failure of the exam or failure of the course.

Land acknowledgement#

UBC’s Point Grey Campus is located on the traditional, ancestral, and unceded territory of the xwməθkwəy̓əm (Musqueam) people. The land it is situated on has always been a place of learning for the Musqueam people, who for millennia have passed on their culture, history, and traditions from one generation to the next on this site.

It’s important that this recognition of Musqueam territory and our relationship with the Musqueam people does not appear as just a formality. Take a moment to appreciate the meaning behind the words we use:

TRADITIONAL recognizes lands traditionally used and/or occupied by the Musqueam people or other First Nations in other parts of the country.

ANCESTRAL recognizes land that is handed down from generation to generation.

UNCEDED refers to land that was not turned over to the Crown (government) by a treaty or other agreement.

As you proceed through your journey at UBC, take some time to learn about the history of this land and to honour its original inhabitants.

Contents