Grading

The grading for this class will comprise of the following continuous assessment milestones, inclusive of two exams. Both exam assessments will largely be MCQ/MRQ based.

DescriptionPercentage
Midterm Exam (Mon, 26 Sep 2022 @ 16:00–17:00)20%
Final Exam (Mon, 21 Nov 2022 @ 17:00–19:00)35%
Machine Learning Project25%
Individual Assignment10%
Participation (Tutorials, Pre-lecture and In-lecture Activities)10%
Total100%

This module will be taught synchronously through Zoom or through live in-place lecture at the LT (where allowed). This iteration will not be conducted in a flipped style, unlike previous iterations. Recordings of the class will be taken, and are likely (but not guaranteed) to be offered in the Conferencing component. Students are expected to be available for both lecture hours and their respective tutorial slots. Tutorials will involve a mix of activities; activities are likely to vary week to week.

Lecture and tutorial attendance is not mandatory, but will help with your participation grade. Participation is very helpful for your teaching staff too. Without it, we have very little idea whether you understand the material that we’ve presented or whether it’s too difficult or trivial. Giving feedback in the form of questions, discussion provides us with a better idea of what topics you enjoy and which you are not too keen on.

Academic Honesty Policy

Please note that we enforce these policies vigorously. While we hate wasting time with these problems, we have to be fair to everyone in the class, and as such, you are advised to pay attention to these rules and follow them strictly.

Collaboration is a very good thing. Students are encouraged to work together and to teach each other. On the other hand, cheating is considered a very serious offense. Please don’t do it! Concern about cheating creates an unpleasant environment for everyone. You will be automatically reported to the vice-dean of academic affairs if you are caught, no exceptions will be made for any infractions no matter how slight the offense.

So how do you draw the line between collaboration and cheating? Here’s a reasonable set of ground-rules. Failure to understand and follow these rules will constitute cheating, and will be dealt with as per University guidelines. We will be enforcing the policy vigorously and strictly.

You should already be familiar with the University’s honor code. If you haven’t yet, read it now.

The Pokémon Go Rule: This rule says that you are free to meet with fellow students(s) and discuss assignments with them. Writing on a board or shared piece of paper is acceptable during the meeting; however, you may not take any written (electronic or otherwise) record away from the meeting. This applies when the assignment is supposed to be an individual effort. After the meeting, engage in a half hour of mind-numbing activity (like catching up with your friends and family’s activities on Facebook, before starting to work on the assignment. This will assure that you are able to reconstruct what you learned from the meeting, by yourself, using your own brain. The Freedom of Information Rule: To assure that all collaboration is on the level, you must always write the name(s) of your collaborators on your assignment. Failure to adequately acknowledge your contributors is at best a lapse of professional etiquette, and at worst it is plagiarism. Plagiarism is a form of cheating.

The No-Sponge Rule: In intra-team collaboration where the team, as a whole, produces a single “product”, each member of the team must actively contribute. Members of the team have the responsibility (1) to not tolerate anyone who is putting forth no effort (being a sponge) and (2) to not let anyone who is making a good faith effort “fall through a crack” (to help weaker team members come up to speed so they can contribute). We want to know about dysfunctional team situations as early as possible. To encourage everyone to participate fully, we make sure that every student is given an opportunity to explain and justify their team’s approach.

This section on academic honesty is adapted from Surendar Chandra’s course at the University of Georgia, who in turn acknowledges Prof. Carla Ellis and Prof. Amin Vahdat at Duke University for his policy formulation. The origin of the original rule, called the Gilligan’s Island rule, is uncertain, but at least can be traced back to Prof. Dymond at York University’s use of it in 1984.

Late Submissions

All homework assignments are due by 23:59:59 (Singapore time; SGT) on the due date. No exceptions without a medical certificate will be made.

Late submissions are penalized as 5% off per day late, capped to a maximum deduction of 40% of the total marks.

Assignment return policy and regrades

All students have a right to question the grading of their work. If a regrade is sought for a particular milestone, this must be brought to our attention within 3 days of the return of the preliminary grades by email. Requests later than that will not be entertained without certified medical leave or school permission.