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dahyun:
Subject Code/Name: ECON20002 - Intermediate Microeconomics

Workload:  2x 1 hr lecture, 1x 1 hr tutorial per week

Assessment: 

* Written Assignment 1 (10%)
* Midsem test (20%)
* Written Assignment 2 (10%)
* Exam (60%)Lectopia Enabled:  Yes, with screen capture. Lectures were all pre-recorded (i.e. no live lectures)

Past exams available: None, only a sample exam. More on this later

Textbook Recommendation: Microeconomics: Global Edition, Ninth Edition, Robert S. Pindyck and Daniel L. Rubinfeld, (2017). Not needed at all, lecture notes were comprehensive enough and the lecturer himself said they were just 'recommended' not required. To be honest microeconomics at this level pretty much follows Hal Varian's Intermediate Microeconomics: A Modern Approach, so if you really want more reading then that's a good place to start.

Lecturer(s): Joshua Miller

Year & Semester of completion: 2021 Semester 1

Rating: 4/5

Your Mark/Grade: H1

Pre-requisites: ECON10004 - Introductory Microeconomics

Comments: This is required for any economics major. This subject runs also during the summer term. Note that Intermediate Macroeconomics does not require this subject as a pre-requisite.

Lectures and content
This subject delves a lot more into microeconomics as advertised. You'll learn a lot more about the intricacies of how consumers and suppliers interact with each other in the market in various ways, and also learn some new concepts. I think it is worth mentioning that there is no game theory in this subject, unlike its introductory counterpart.

Joshua is a new lecturer for this subject, and has revamped the subject quite a bit. Looking at past reviews this subject seemed to be a "WAM booster" but I can assure this is not entirely accurate anymore. The lecturer is very passionate about economics and developing both economic and mathematical intuition of concepts. I really appreciated this, since I would always get the mathematical intuition, but never the economic! Otherwise though, this is an interesting subject and you'll learn quite a bit from it.

Lectures themselves were broken up into short videos. They actually never summed up to 1 hour per "full lecture", but this is honestly a lot better than having a straight-up 1 hour lecture. It makes it easier to focus on a specific part of the lecture.

Let's talk about content: in twelve weeks, you'll learn about:
Week 1 - Supply and Demand
SpoilerThis is just a recap of intro to micro - elasticity, supply and demand equations, equilibrium price + quantity. By far the most easy week and you'll probably won't be tested on this directlyWeek 2 - Consumer preferences and budget constraints
SpoilerThis week introduces the concepts of consumer preferences (if given two goods, which one would the consumer choose and how many would they want?). Essentially this is an 'application' of marginal benefits and marginal costs - a VERY RE-OCCURRING CONCEPT THAT I STRONGLY ADVISE YOU TO REMEMBER AND UNDERSTAND!!!Week 3 - Consumer choice
SpoilerElaborates a bit more upon week 3's consumer preferences - this is the bulk of the mid-semester and perhaps assignment 1 content. I think this is the week you learn about marginal rate of substitution, which is actually the most important concept in this whole subject.Week 4 - Individual demand, income and substitution effects and intertemporal consumer choice
SpoilerA big week actually, but the first part is just understanding what happens when a supply/demand curve shifts (lower income? lower supply?). Intertemporal consumer choice is just consumer choice but with respect to time - so we add in interest rates and price baskets. Mathematically, this is somewhat similar to Principles of Finance stuff but it's quite intuitive anyways so don't worry. Week 5 - Equilibrium Analysis and Efficiency in Exchange
SpoilerThis is a very tricky week in my humble opinion. Edgeworth boxes are very tricky to understand for myself and there was a 10 mark question about it on the exam that I didn't do...but it's not too bad otherwise this week. Week 6 - Uncertainty and Consumer Behaviour
SpoilerBy far my most favourite week since this introduced the concept of uncertainty with consumer behaviour. You learn about risk and actuarially fair premiums. I thought I left actuarial for good! The second assignment was about this week. Week 7 - Production and Returns to Scale
SpoilerAfter spending half the term on consumers, we now move towards producers. Learn the basics of producer theory and how they interact in certain markets, along with short-run and long-run introductions. Week 8 - Cost of production
SpoilerIt takes money to make stuff! Learn how producers minimise costs in a plethora of ways!Week 9 - Profit Maximisation
SpoilerA very interesting point that Joshua made was how minimising costs does not always imply profit maximisation. It turns out (spoilers!) that this is true when marginal revenue is equal to marginal cost...I think. It's been a while sorry hahhaahha Week 10 - Monopolies and Price Discrimination
SpoilerLearn why monopolies are bad for consumers but good for suppliers, and how monopolies price according to their consumer base (first degree/second/third degree price discrimination). I think this was covered back in intro to micro. Corporate restructuring
SpoilerLearn how companies change their internal structure, why and how they do it! Not too much about this week from memory but still pretty important. Week 11 - Oligopoly
SpoilerWhilst monopolies are basically banned from ever happening, oligopolies are a bit more doable. Learn how two companies try and maximise profits - through collusion or not. You also learn about Bertrand competition, and Cournot competition, along with sequential game competition. This is the closest to game theory you'll get here!
Tutorials
This subject was held entirely online. I did not go to any tutorials past week 4 since I could not be bothered. They help, and they are the only way of getting in-tutorial answers. Even then, you had to take photos or write super fast as the tutors would not send their answers afterwards. (perhaps some did, but for most they didn't). The pre-tutorial questions were quite good for the most part, and their answers were released after the week ended.

Assessments
The first assignment was about week 2-3 (maybe 4?). I didn't really do well on here, but it was an easy assignment for the most part. Many of my friends scored their highest mark here, so just keep up to date and don't leave things to last minute!

The mid-semester test examined weeks 1 - 5. This was a fair test, but some of the questions in the question bank (people didn't have the exact same MST as each other) were quite hard. There was also an issue with the first question regarding ambiguity of answers, so we all received +6 marks on our MST. This was great since I had no idea how to answer it anyways. My best tip is to just do all the tutorial questions. There are only so many ways they can ask you a question before they repeat themselves!
 
Assignment 2 was pretty tough. I spent the bulk majority of the two weeks working on it alone (you can do assignments in groups or individual, like intro to macro). Based solely from week 6 (uncertainty), it expanded a lot further beyond the tute questions, so a lot of research was needed.

Something I have yet to mention is that this subject used Edstem as our discussion board. It is super useful and hopefully all subjects implement this, instead of the archaic looking and feeling online tutor.

The final exam (60%) was not bad actually. 60 marks in total, with 6 questions each worth 10 marks. They tested most of the weeks, especially on the weeks which didn't have an assignment about it (i.e. uncertainty was not on it :( ). To prepare for this: do the sample exam (past exams IMO never help when we have a new lecturer/format), do ALL the tutorial (pre and in-tute), and try to understand what you're doing. Ask freely on Edstem and go-to consults if needed and you'll be very fine for the exam.

Bonus: I think Joshua sent 20+ announcements leading up to exam about how it'll run and how to upload it. This was very annoying but understandable. We just had to handwrite (on tablet or paper) and upload it to Gradescope and match the pages.

Concluding remarks
Pretty alright subject content-wise, and decent lecturer and subject team. I only wish that there will be less announcements for any future cohorts. I would try and do this subject over summer! On-to intermediate macro now!

Duckhole:
Subject Code/Name: BIOM30002 - Biomedicine: Molecule to Malady

Faculty: MDHS

Workload:  Three 1-hour lectures per week plus six 1-hour tutorials per semester.

Assessment:  x2 Multiple choice MSTs throughout the semester, each worth 20% (40% in total). End of semester exam worth 60%, with SAQ component worth 40% and MCQ component worth 20%.

Lectopia Enabled:  All lectures delivered live via Zoom. Recorded and uploaded onto lecture capture.

Past exams available:  No past exams made available but a sample SAQ exam was provided beforehand.

Textbook Recommendation:  No recommended textbook but the Janeway's Immunobiology textbook that is recommended for Principles of Immunology is quite useful for a lot of the modules given that the subject is quite heavy on immunology.

Lecturer(s): Multiple guest lecturers for each module.

Year & Semester of completion: Semester 1, 2021

Rating:  4.5 Out of 5

Your Mark/Grade: H1

Comments: I'll give a general overview of the subject, followed by more specific information about the different modules. It looks like there haven't been many reviews for this subject in more recent times so I'll try to include some information about what might have changed. Overall I found this subject to be very enjoyable, possibly my favourite subject of the semester. This subject focuses on five different "maladies" with various guest lecturers who research these specific diseases delivering the lectures so you really get to sample the most up to date scientific information and recent developments in the field. This year, we covered B-cells, cystic fibrosis, pandemics, rheumatoid arthritis and type 1 diabetes. For each module we also had interviews with patients who came and talked to us about their experiences living with the disease and personally I thought this was a highlight of the subject.

The modular structure of the subject is really useful for revising the content later on. Jessica Welch, the subject coordinator, is an incredibly lovely person and is very approachable. All lecture recordings are were uploaded in a timely manner, typically 30 minutes after the live lecture concluded (all lectures were delivered live via Zoom). Feedback quizzes for each module were made available, as well as FAQs from the live lectures. I believe relevant journal articles and research papers were also made available as recommended readings but I didn't really use these. Extensive feedback for each MST was given, including a very thorough analysis of the overall cohort performance and Jess was also very transparent about how the questions are subjected to 'quality control' after marking to make sure assessments are as fair as possible. Needless to say, subject coordination was impeccable.

B-cells
This entire module was taken by Dr Vanessa Bryant. This was my favourite module of the subject, but this may be because I'm biased as an immunology major. This module can be generally divided into two subsections, with the first half of the module focusing on primary immunodeficiencies that affect B-cell function, and the final two lectures covering the therapeutic applications of antibodies, particularly the importance of broadly neutralising antibodies in the context of HIV. We covered four different immunodeficiencies in detail as well as a more general overview of how B-cells develop in the bone marrow. This is probably obvious, but this module delves quite deeply into immunological concepts like VDJ recombination and the formation of germinal centres, etc. I think a lot of people who aren't accustomed to immunity initially found this module to be challenging because of this so would definitely recommend brushing up on all the immunological concepts you went through with Odilia in MCB. Can be quite complex, particularly with the bNAbs lecture, and may need a few rewatches and extra time spent outside the lectures just really drilling the basic immunology of it into your head. Once you understand it though it's really not too bad in terms of the amount of content.

Cystic Fibrosis
We had two lecturers for this module: Dr Chloe Stutterd for the first half and Dr Jo Harrison for the second half. Chloe kicked off the module with the genetic and molecular basis of Cystic Fibrosis, where we went through the different mutations that lead to CF and genetic and environmental factors that affect the disease phenotype. We also went through the structure of the CFTR protein and how its functions become aberrant in disease, leading to the clinical manifestations of CF. Jo then went into more detail about the clinical features of CF, firstly covering the pulmonary aspects of CF, followed by non-pulmonary aspects and therapeutics/management of CF. Wasn't too bad in terms of detail or complexity and the content was interesting.

Pandemics
The largest module of the semester where we covered three major human pandemics with three lectures for each: Malaria, HIV and COVID-19.

For malaria we had Prof. Brendan Crabb and covered the epidemiology/natural history of malaria in the first lecture as well as some features of the malarial parasite and how it causes disease. The next lecture mostly focused on drugs to treat malaria and potential drug targets whilst the final lecture focused on vaccines against the disease and the different approaches that have been adopted for vaccination.

The HIV component was taken by Prof. Sharon Lewin and again followed a similar structure to the malaria lectures, with the first lecture covering epidemiology of HIV, as well as virology and immunology. The second lecture focused on current treatments and we briefly touched on vaccine approaches, whilst the third lecture focused on a HIV cure for the first half before finishing off with a patient interview.

Lastly, we finished off the module with COVID-19, with two lectures from Prof. Damien Purcell and a lecture by the coordinator Jessica Welch. The two lectures focused on the virology of COVID-19 and its pathogenesis whilst the second lecture focused on vaccine strategies. Lastly, Jess went through infection control strategies for COVID-19 and we briefly looked at case studies of the public health approaches adopted by different countries that were successful in controlling COVID-19.

Rheumatoid Arthritis
In my opinion, this was the most difficult module to get through. First few lectures were taken by A/Prof Natalie Sims who covered bone and synovium health. This was okay-ish but having to remember the inflammatory cytokines and the cells involved was a bit hectic. Nevertheless, Natalie was very easy to understand and presented her content clearly and succinctly. The other lectures in this module were presented by Dr John Moi, who spoke more about RA symptoms and associated deformities, epidemiology, risk factors, before finishing up the module with lectures on treatment, focusing specifically on TNF-a blockers. That final lecture was a doozy and went into a deep dive into many different monoclonal antibodies as well as the head-to-head clinical trials conducted for each of them. The final exam examined these concepts in a lot of detail too and this module was by far the most content heavy in my opinion.

Type 1 Diabetes
A really fascinating module. Like with most of the modules, this was a very immunology heavy topic. Our primary lecturer was Dr Tom Brodnicki who took us through the general history of T1D, its autoimmune basis, as well as how NOD mouse models have influenced T1D research. The stuff on autoimmunity was very interesting but also complex and initially difficult to understand, but Tom does a good job of explaining it. The last two lectures, one of which was a patient interview, were taken by Prof. Tom Kay. We finished up the module exploring the most current research into a cure for T1D.

In summary, a well-coordinated subject which can be quite content heavy at times but definitely manageable with consistent work.

hums_student:
Subject Code/Name: ECOM30002 / ECOM90002 Econometrics 2

Workload: 1 x 2 hr lecture and 1 x 1 hr tutorial per week

Assessment:
- 4 group assignments worth 7.5% each (can be done individually if you dare)
- Final exam worth 70%

Lectopia Enabled: Yes, with screen capture

Past exams available: Yes, we were given the 2020 Semester 1 exam and half of the 2016 Exam.

Textbook Recommendation: Introduction to Econometrics, 3rd Edition by Stock and Watson

Lecturer(s): Matthew Greenwood-Nimmo

Year & Semester of completion: 2021 Semester 1

Rating: 4.5 out of 5

Your Mark/Grade: H1 (90)

Comments

Matt was a fantastic subject coordinator and he made the subject content incredibly straightforward. I only joined the subject in Week 3 so at first I was quite worried about how behind I was going to be, but despite horror stories of how difficult ECOM 2 was, I found the content was taught in a very simple and easy-to-understand method.

Despite that, it was a still a major step up from Econometrics 1. The maths was very easy but I struggled a lot with the coding component, particular the Monte Carlo simulations. Coding isn't on the exam but it is a major part of all 4 assignments, particularly the last two, where the codes become a lot more complicated than the usual regression analysis most people were used to from Econometrics 1.

In terms of content, the subject was split into 3 topics:
   1. OLS and 2SLS regressions
   2. Panel Data
   3. Time Series

I can't say much about tutorials because I didn't go to any of them after 2 weeks. Daniel Tiong (tutorial coordinator) uploaded videos of him going through each tute sheet every week and those were infinitely more helpful.

As for the exam, it's pretty much structured like the course content. There are 4 questions, the first two corresponding to topic 1 (Q1 gives you a real life situation and asks you to interpret the regressions, Q2 gives you a Monte Carlo simulation). Q3 and Q4 are on Panel Data and Time Series respectively.

My one complaint regarding this subject was that we never received any personalised feedback on assignments. Matt provided detailed sample answers, but it was still frustrating getting back an assignment that I scored 76% on and seeing zero feedback on my actual response - not even a slight indication of where I lost marks on. I know some other groups received some feedback, but it would've been great if that had been consistent across all tutors marking.

Overall, though, ECOM was a very enjoyable subject. I'll end this review with some screenshots of our discussion board taken the night before our final exam to sum up the unit.

Tau:
Subject Code/Name: COMP10002 Foundations of Algorithms

Workload:
- 3 one-hour lectures
- 1 two-hour workshop

Assessment:
- 2 assignments (15% each)
- 1 Mid Semester Test (10%)
- Exam (60%)

Past exams available:
Yes, sample exam with solutions, a handful of others without.

Textbook Recommendation:
Programming, Problem Solving & Abstraction with C by Alistair Moffat. Excellent textbook imo, definitely worth reading.

Lecturers: Shaanan Cohney & Jianzhong Qi

Year & Semester of completion: 2021 Semester 1

Rating: 4.5 out of 5

Your Mark/Grade: H1
Comments:

Course Structure
The course starts with an introduction to what algorithms are, and an exploration into programming in C (which is a lot more to-the-metal then Python). C is beautiful but painful, it's easy to shoot yourself in the foot (and you will at first, all the time), but it also has a certain simplicity and power that it enables that is wonderful. The introduction to C and the first 4ish weeks of semester are too slow imo. Learning how the handling of pointers and dynamic memory allocation in C can enable recursive data structures was a really nice moment for me. Big O Algorithmic complexity is covered in the typical non-mathsy slightly-handwavy manner. There's a few string search algorithms and the common sorting algorithms covered (QuickSort, MergeSort, Bubble Sort, Heap Sort, Insertion Sort), but this knowledge doesn't every really seem to be directly tested on (just how to use library functions for them). I do feel like there's more focus on the coding than there is on the algorithms themselves, which I understand is a known 'issue', but is regardless still decent coverage at an introductory level.

My thoughts:
I don't really have anything to fault in this subject other than that overall, I got fairly bored quickly and didn't really show up to any of my workshops and had to painstakingly force myself to watch the lectures. I just felt I'd do better by just reading the textbook or online resource and then just attempting the assignments (which worked for me). It's a good introductory algorithms subject that's well taught and coordinated.

Lectures
Lectures were split by both lectures, with Jianzhong taking over after the mid-sim break. Shaanan was a new lecturer for this year, and did an absolutely excellent job. Jianzhong I understand has taught this subject multiple times, and brought lots of experience. They were both excellent, super super happy to help anyone out, answered questions on Piazza breathtakingly fast, took onboard feedback, and were overall a pleasure to have teaching and coordinating. (Having said that, I admittedly skipped multiple lectures, no reflection on the lecturers themselves. )

Workshops
2 hour session, going through some content followed by individual work on problems on Grok. My tutor was good, and I have no issues with how they were run, but I stopped attending after Week 4 as I felt I'd rather spend that time woking by myself (which admittedly mostly involved me doing nothing instead) and I just wasn't getting much utility from them.

Assignments
Assignments are fairly long programming tasks, that take quite a while. Emphasis here is more on C - the more fluent your C, the faster you'd finish. I managed to drop 1/2 mark on each, from minor things, and as long as you think carefully about your solution correctness you can do well. I learn a lot from doing them though, as they forced me to actually practice.

Exam
The exam definitely felt fairly long, and it seems like many (most) didn't complete the exam. This semester it was all via Canvas quizzes (IDE and any resources allowed), with mostly straight programming implementation questions. Didn't do as well in the exam as I'd have liked, but then I'm much better at maths exams then programming under time constraints.

Tau:
Subject Code/Name: COMP20008 Elements of Data Processing

Workload:
- pre-recorded lectures, 1 hour live lecture
- 1 one-hour workshop

Assessment:
- 1 individual assignment (20%)
- 1 group assignment (30%)
- Exam (50%)

Past exams available:
Yes, sample exams without solutions.

Textbook Recommendation:
None.

Lecturers: Pauline Lin and Chris Ewin

Year & Semester of completion: 2021 Semester 1

Rating: 0/5

Your Mark/Grade: H1
Comments:

My thoughts:
Oftentimes rude or unhelpful tutors, inconsistent and contradictory replies, doubling down on their assignment specification instead of clarifying what was clearly an error. Pretty poor lectures, useless workshops. Content that is overall just below the surface of a good Google search. Hell, Foundations of Algorithms is a 1000x better course and curriculum with useful content, at a level 1. You’d hope at this stage a level 2 subject would at least be more worthwhile. Honestly they could scrap the entire subject and there’d be no substantive change.

I don't really want to go into it any more since the whole subject was just terrible. My advice: if you can avoid it, don't do it and just use the time to google everything instead (literally what you'd be doing anyways).

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