Carleton Bird Courses

A reflection on the course I have taken

Posted by Krystian Wojcicki on Tuesday, January 18, 2022 Tags: School   5 minute read

Introduction

Disclaimer: I am a Computer Science Student who enjoys math and coding and my opinion on courses reflect this, I also do have a A+ CGPA so take that as you will. I would not recommend any COMP course to non-Computer Science students. But I have heard good things about Introduction to Computer Science classes. Most first year course are relatively free and I won’t comment too much on those. In addition I have been going to Carleton for over 4 years, class structures may have change or professors could have changed.

Course I have taken:

  • BUSI 1003
  • COMP 1405: those who are technically inclined or curious, I believe can do perfectly well in this course. If I recall correctly over 50% of my class had never coded before entering that class. Having a basic understand of coding can be a HUGE asset for anyone.
  • PHYS 1007
  • MATH 1007
  • COMP 1406
  • COMP 1805: has a reputation for being a difficult course. I think this is because, for many, almost all the entire material is completely new and somewhat tough to learn by yourself. Personally enjoyed the course quite a lot, and it will be helpful for this hoping to excel in theoretical and practical Computer Science. Here is a great resource for those struggling with COMP 1805.
  • ECON 1000: many upper year economic courses are quite easy and typically first year economics is a prerequisite, so I would recommend.
  • MATH 1104
  • PHYS 1008
  • COMP 2401: poorly designed course but is mandatory.
  • COMP 2404: poorly designed course but again is mandatory. Maybe we should start learning beyond that which was invented in 1998? C++17 please? Or atleast C++11.
  • COMP 2402: amazing course, especially with Pat Morin, super useful. Don’t focus too much on the proofs, but the bigger picture.
  • COMP 2406
  • MATH 2007: same as MATH 1007 but a bit more, shouldn’t be too challenging for STEM students. Calculus is useful for those looking to go further in AI.
  • MATH 2107: challenging course for those outside of STEM or even for some inside of it. For Computer Science students (or AI enthusiasts) who are looking to be a cut above the rest, I would recommend it.
  • COMP 2804
  • PHIL 2001: must take for those who have taken COMP 1805, for those who have not this is still a simple course assuming one is okay with boolean logic: ie
B and A
A
____
B
  • PHIL 2003: an interesting class dealing with a wide variety of topics from deductive reasoning, inductive reasoning, logical fallacies. May be challenging for some but definitely enjoyable
  • STAT 2507: mandatory course for many people, not particularly interesting. Easy course if one is okay with memorizing formulas and simply plugging numbers into a calculator.
  • CGSC 1001: very interesting class, covering multitude of subjects at a surface level. Very easy and not too much work.
  • COMP 3000: seen a huge variety in the content of the course and tough to comment.
  • COMP 3004: unfortunately a mandatory course, I hope one day Carleton rethinks this course. Its pitiful how much time is wasted learning absolutely nothing. A disgrace. I could write an entire essay on why this course fails to provide any educational value.
  • COMP 3005: another course that is a complete waste and needs to be recreated.
  • COMP 3007:
  • COMP 3804: a challenging course, can take some time for the concepts to click. Will be beneficial if one has a background in proofs. Challenging but rewarding and those striving for FAANG interviews will benefit greatly from this.
  • COMP 4107: amazing course, specifically if taught by Tony White, will involve lots of work (especially if one has never worked with neural networks/ML before).
  • ECON 2009: very easy course, memorize formulas then do basic plug and play.
  • ERTH 2415: very easy course requiring lots and lots of memorization. Semi interesting content.
  • LING 1001:

Courses I am taking:

  • COMP 4106: has some interesting nuggets of information, not a difficult course by any stretch
  • COMP 4900B Introduction to Machine Learning: a difficult course should only be taken by those actually interesting in machine learning.
  • LING 1100: Ai Taniguchi makes this course very enjoyable and approachable for anyone.
  • MATH 3800: a slightly disappointing course for those who are actually there to learn, simply memorize formulas and go to town. Would recommend for any STEM students looking for an easy A+ https://www.youtube.com/watch?v=pvimAM_SLic
  • PHIL 2700: I took the completely online version of this, if one wants its an easy A with minimal effort. But has to ability to be an interesting course if one chooses.
  • STAT 2509: your given a formula sheet and then you put #’s into that formula, its not hard. Would recommend if your looking for an easy grade and not much learning.

Courses I have not taken but have heard about:

  • ERTH 2401: lots and lots of memorization of not particullary interesting material
  • GEOG 2200: not challenging but not interesting