General Information

  • Time : Tues. and Thurs. 11am-12:30pm
  • Location : DMP 101
  • Instructor : Frank Wood
  • Email : fwood@cs.ubc.ca (use [CS532W Prob Prog] in subject line)

Grading

Grading of graduate course work is an unfortunate reality. The relative weighting of the individual contributors to the grade are as follows:

  • Participation: 5%
  • Homework: 70%
  • Project: 25%
    • of which
      • Proposal: 20%
      • Report: 70%
      • Final presentation : 10%

The final grade assigned will be based on a curve. Students’ final numerical scores will be sorted and then, based on their ranking, students will be assigned to grade bins with roughly 50% receiving an A, 40% receiving a B, and the remainder a lower or failing grade. The instructor reserves the right to given everyone an A, fail everyone, or assign any other relative proportions of grades to rankings.

Prerequisites

I am of the opinion that almost anybody, with sufficient time, could make it through the course, however, some experience dictates that those without a strong programming languages, Bayesian statistics, and general machine learning background will struggle. As well, very strong programming skills are required.

  • Minimal: CS440, CS110 (or equivalent)
    • (advanced machine learning, functional programming)
  • Ideal: another advanced machine learning version of CS532, an advanced Bayesian statistics class (STAT520a), and CS511 (or concurrent)

Policies

Academic Integrity

Absolute academic integrity is expected of all UBC students in every academic undertaking. UBC gives wide discretion to the course instructor to define what constitutes integrity, i.e. honest and responsible scholarship, in their course.

In this course are expected to work collaboratively on coding exercises but hand in work that is entirely your own. General discussions with other students are encouraged, and even discussion about problem specifics, but, the final code must have been written by you in its entirety.

You are specifically not allowed to:

  • Search the internet for existing solutions.
  • Share solution code, either in part or in whole.
  • Directly manually translate code written in other languages on the internet.

The project in this course is a group project. You are required to work in good faith with your groupmates, to contribute approximately equally, and to completely honestly make explicit what contribution came from whom.

If it is unclear what is allowed and what is not, please ask!

Penalties for violations of academic integrity standards are quite severe and can result in failing the course or being expelled from your program.

Positive Space

Our classroom is a positive space. If you are harassed or made to feel uncomfortable please bring it to the attention of the instructor immediately. If it is the instructor who is the cause, please immediately bring it to the attention of your departmental advisor or the computer science department chair.