BCom Subject Review 2026 S1 - (Probability, RealAnalysis, FOC, IFM)
Each subject review includes my own result (to anchor expectations) and a “Difficulty Rating” which ranges from 0/10 (extremely easy), 5/10 (doable, think: Calc2/LinAlg), to 7/10 (hard, think: Intro Macroecon), to 10/10 (nightmare fuel, think: Principles of Finance). Obviously my opinions are my own only, and may not reflect others’ experiences.
ACTL20001 Introductory Finance
Coordinator/Lecturer: Ping Chen
Difficulty Rating: 9/10, Recommended: 10/10 (if you have the guts for it!)
Teaching Activities Per week: 2x 1 hour Lectures, 1x 1 hour Tute
Assessment: 2 Assignments (30% Total), Final Exam (70%, Hurdle).
One of the most challenging and rewarding subjects I’ve ever done in university. The course begins with an introduction to interest rates and different ways of describing it, such as simple/compound/nominal (and equivalent discount). Then discusses different financial products like stocks and bonds, as well as pricing financial products and cash flows.
Lectures are extremely fast paced and I struggled greatly to keep up with the speed and depth with which Ping goes through things. However, once I began to slightly understand the content, it was really interesting and very rewarding to keep learning. The final exam reflects the difficulty of the course content and I struggled greatly with time pressure and couldn’t finish the paper. I believe there was no scaling. Still I’m grateful for having this opportunity to test my absolute academic limits, and although I didn’t do as well as I wanted (due to an insufficient amount of both talent and effort), the intensity of this experience has shaped my character.
MAST20004 Probability
Coordinator: Peter Taylor (& Sophie Hautphenne also a Lecturer)
Difficulty Rating: 7/10, Recommended: 9/10
Teaching Activities Per week: 3x 1 hour Lectures, 2x 1 hour Tutes (1 of them a R computer lab)
Assessment: 4 Assignments (20% Total), Final Exam (80%).
This course is an (initially) gentle but rigorous introduction to the concepts of probability, and some related ideas. The course starts with defining “axioms” related to probability, some general properties of it, and then discusses different types of “special” probability distributions as well as ways to calculate/describe probability, and what a random variable is. Concepts like “mean” and “variance” are also mentioned. Towards the end there’s also a bunch of tangential stuff such as Chebyshev’s inequality, different limit theorems, and covariance. However they’re not assessed very heavily. The exam was accessible, with most questions being surface level and easier than the tutorial questions (There are some challenging ones meant to separate the very top students, where most people including myself just skipped/couldn’t start).
Overall, I scored in the low 90s & (in terms of revision) would mostly recommend memorising the key formulas from lectures and know how to apply them without making mistakes. You can also try to do the “Problem Booklet” however that’s mostly reserved for the top students (I couldn’t do the majority of those questions & towards the end, most of them are so complex/extension that I wouldn't even bother trying), the exams are not nearly that level of difficulty. Understanding the lecture formulas & applying them to tutorial questions should be sufficient to do decently. You are allowed to bring a 2 page cheat sheet.
MAST20026 Real Analysis
Coordinator/Lecturer: Alex Ghitza
Difficulty Rating: 7/10, Recommended: 7/10
Teaching Activities Per week: 3x 1 hour Lectures, 2x 1 hour Tutes
Assessment: 4 Assignments (20% Total), 10 Online Quizzes (10% Total), Final Exam (70%).
The course covers (in order): basic formal logic, sets, sequences, functions, integration, and series. It mostly expands upon Calculus 2 and delves into different proof techniques. There are 2 tutorials each week and sometimes cover content that was not mentioned in lectures (the first time I’ve experienced this in a MAST subject). The content is hard to follow and the proofs done are often presented / understood in a very confusing way. However, the lecturer is engaging and did their best. The assignment questions are very difficult and extend beyond what is done in Lectures. This sem is notably different from previous years as there was less focus on the algebra axioms, and more on the “analytical” stuff such as continuity and convergence. There’s also less of a focus on traditional “epsilon” “delta” proofs in favour of a wider range of different theorems, making this sem more content heavy than past papers.
I found the exam tough with serious time restraint, and some questions felt quite inaccessible. But overall it was reasonable, with (presumably) very VERY heavy scaling applied to the final result, I scored in the low-mid 90s despite doing much worse than that on the exam. Overall, even though this subject is not compulsory for the Bachelor of Commerce, I’d recommend it for some Econ & Finance majors who wish to build up mathematical rigour / ability, before taking on the nightmare that is level 3 econ/finance.
COMP10001 Foundations of Computing
Coordinator: Chris Ewin, Geela Chee
Difficulty Rating: 4/10, Recommended: 8/10
Teaching Activities Per week: 3x 1 hour Lectures, 1x 2 hour Tute
Assessment: 2 Assignments (30% Total), MidSem Test (10%), Worksheets (10%), Final Exam (50%, Hurdle).
Introduces students to the basics of Python programming and is designed for those with zero computing/coding experience whatsoever. The course starts gently from basic items in the language in the first 3 weeks, then stuff like statements/loops in the middle, then more advanced stuff like recursion & writing actual code that does stuff. The lectures don’t really follow the slides but are mostly the lecturers writing code in front of you and running it to demonstrate different things. The MST and Final both include a lot of questions asking you to write 1-line expressions, or evaluating the output of certain expressions. If you get a good grasp on those you’ll bag a good portion of the marks. The 2 assignments allow you as much time as you want to work on them, so if you can get good marks on those you can scrape an H1 regardless (In my case I put in good effort to score highly on the project, which allowed me to get mid-80s overall despite doing wayyy worse on the final).
Despite this being my worst result this sem (which contradicts me giving this the lowest Difficulty Rating out of the 4 subjects), I’d like to say that this is fully my own fault for not putting in any of the work, not going to any of the tutorials, and not watching the last 3 lectures. The subject itself is very well-designed and heavily rewards those that work hard, and (in my case) punishes those who don't. Very recommended for those looking to make a start on programming.