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 121

CPSC 330 102

Tue/Thu

11:00 - 12:20 PM

SWNG 221

Tutorials and office hours:

To find tutorial schedules and office hours, please refer to the Calendar. 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.

Teaching Team#

Instructors:

Course co-ordinator#

  • Michelle Pang (cpsc330-admin@cs.ubc.ca)

TAs#

  • Chen Liu (chenliu5@student.ubc.ca)

  • Justice Sefas (jsefas@cs.ubc.ca)

  • Mahsa Zarei (mzarei@chem.ubc.ca)

  • Miranda Chan (mc835@student.ubc.ca)

  • Vee Rajesh Bahel (bvedant@cs.ubc.ca)

  • Wilson Tu (linshuan@student.ubc.ca)

  • Yeojun Han (yeojunh@student.ubc.ca)

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%

Canvas

iClicker participation

2%

iClicker Cloud

Worksheets

5%

Gradescope

Assignments

20%

Gradescope

Midterm

22%

Canvas

Final

50%

Canvas

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. However, this is not finalized yet. For example, the last assignment ends up particularly short or long due to timing. Furthermore, 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 5 minutes before midnight on the due date.

If you can’t make it, you can use late classes:

For example, if assignment is due on a Monday:

  • Handing it in Tuesday is 1 late class.

  • Handing it in Thursday is 2 late classes.

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

  • Use more than 2 late classes on the assignment.

  • Use more than 4 late classes across all assignments.

If you are working in a pair, you both must have late classes remaining.

We will posting solutions after the second late class has expired.

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. However, it is not allowed during the midterm 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.

Midterm#

Check the Calendar for midterm date and time. The exam will be on Canvas and you will have 75 minutes to complete it.

Missed midterm exam. There is no makeup midterm exam. If you miss the midterm exam, or anticipate missing the midterm exam, please see the Academic concessions section above. In most cases, if you have missed the midterm exam for a justified reason, the weight of the midterm component of the course will be transferred to the final exam.

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 complete academic concession form, clearly indicating the nature of the concession you are seeking, and send the form via email to the course coordinator, Michelle Pang (cpsc330-admin@cs.ubc.ca), with your 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!

Covid Safety at UBC#

Please read Covid Campus Rules.

Masks: This class is going to be in person. UBC no longer requires students, faculty and staff to wear non-medical masks, but continues to recommend that masks be worn in indoor public spaces.

Your personal health: If you are ill or believe you have COVID-19 symptoms or been exposed to SARS-CoV-2 use the Thrive Health self-assessment tool for guidance, or download the BC COVID-19 Support App for iOS or Android device and follow the instructions provided. Follow the advice from Public Health.

Stay home if you have recently tested positive for COVID-19 or are required to quarantine. You can check this website to find out if you should self-isolate or self-monitor.

Your precautions will help reduce risk and keep everyone safer. In this class, the marking scheme is intended to provide flexibility so that you can prioritize your health and still be able to succeed:

  • All course notes will be provided online.

  • All homework assignments can be done and handed in online.

  • All exams will be held online. (But you need to be present in the classroom to write the exam unless there is a legitimate reason for not doing so.)

  • Most of the class activity will be video recorded and will be made available to you.

  • Before each class, I’ll also try to post some videos on YouTube to facilitate hybrid learning.

  • There will be at least a few office hours which will be held online.