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March 29, 2024, 12:39:09 am

Author Topic: University of Melbourne - Subject Reviews & Ratings  (Read 1734957 times)  Share 

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BuffInvestmentBanker

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #825 on: March 27, 2021, 01:08:14 am »
+4
Subject Code/Name: FNCE30012 Foundations of Fintech

Workload:
chunky 2 hr lecture
1 hr workshop (half the time of this was no coders bitching about the class and then ending with a mid 70 in the end)

Assessment:
Quizzes: 20%
2* Assignments: 20% total
2* Projects: 40% total
Exam: 20% (hurdle)

Past exams available:  No.  This was the first sem with an exam (20% weighted and hurdle wtf??). But it was similar to the weekly quizzes. All theory

Textbook Recommendation:  Lect slides be enough

Lecturer(s): There was a few modules and each module had different lecture. They where all from the famous mind, brain markets lab at melb which is a world class experimental/computational/behavioral finance facility

Year & Semester of completion: 2020 S2

Rating:  5 Out of 5 (organization was meh and tough for neebies to coding but the content was A**)

Your Mark/Grade: 89%

Comments:
If you're a neebie to programming gg bc it's gonna be a wild ride. I'd suggest comp10001 at the min but tbh that should be enough, python for everyone on edx/coursera should be enough as well (self learn that over winter seriously and pay attention and you'll get H1). Personally I did fit1053 (at monash) which is what I'd say is closest to comp10002: foundations of algo but uses python if that make's any sense (tougher class than FoC no doubt)., also did VCE soft dev and self learnt a lot C++ and python throughout high school so I'd define my coding skill as very much above average. However despite being well versed in soft dev in python I learnt a boat load from this class. A lot of interesting machine learning/data sci applied to finance industry, numpy, pandas, and a lot of other libraries. The content was a holistic view of tech in finance from banking to algo trading to machine learning in finance. I interned at as quant trader and I shit you not a lot the content in this class came up and was used during my internship. Personally I'm very interested in quant trading or becoming a strat at an IB so the content in this was sooooo useful.

However it's not an easy class by any means and the assignments/projects where a massive time sink. I actually had some blank questions in my project just cuz I was busy with other classes despite coming from a strong coding background. However given you pay attention in lectures the weekly quizzes should be a free 18/20+ and same goes with the exam.

It might be the wam boost we all need from certain classes (**cough** ARA **cough** OB), but it'll boost your skills and knowledge no doubt. I had a mate who did comp20008 and got 71 in that and got 82 in fintech so it's definitely not an impossible H1 by an means. But the content was soooo interesting (as compared to other finance classes like PoF)

If you're a finance/CS/DS/math student wanting to work in finance (especially trading) take this class, it's a fucking must
If you're a finance student wanting to take a class that actually builds relevant skills that will help in the ever changing industry take this class (like really what you learning in ethics of finance, or int'l finance? python and ML is the future be ahead of the curve not behind it).

Also if you're a non coder none of my mates who a lot don't code got H2B at the very least (these guys have H3 to H2A wams) with hard work you can smash it. I'd say content is like 50/50 coding/theory cuz the quizes and exam is all theory which is 40% and assignments/projects arent 100% code. Also the theory is quite easy, there will be hard coding problems but the theory questions will boost your score a considerable amount dw)
2017 - 2018: VCE:
FM. MM, SM, Physics, Eng lang, Soft dev (ATAR: 98.8 )

2019: BBankFi (Banking/finance and mathematics majors) (Scholars) @ monash (WAM: 88.7)
2020 - 2022: Bcom(finance)/DMath (App math) @ UniMelb (WAM: 87.5)

2021 Classes:
S1 FNCE30001, FNCE30007, MAST20026, MAST30021
S2 MAST30028, ECON20005, FNCE30010, MAST20004

2022 Classes:
S1 ECON30025, MAST30030, ACTL20001
S2 MAST30001, ACTL20003, ACTL20004

GOALS: Graduate with an honours degree and continue a career in quant trading, strat at BBIB, or quant research. Willing to chat about similar interests.

dahyun

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #826 on: June 12, 2021, 02:58:33 pm »
+5
    Subject Code/Name: FNCE20005 - Corporate Financial Decision Making

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

    Assessment: 
    • Mid-semester test (20% of total)
    • Final exam (80% of total)
    Note that the final exam is a hurdle - 50%+ required on the final exam itself in order to pass the subject

    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: Business Finance12e (Peirson et al 2014). Not needed at all - in fact, the online tutors didn't even help those who had problems with the questions in this textbook! Lecture slides are already comprehensive. I'd suggest you search up topics you are not sure about instead!

    Lecturer(s): Chander Shekhar

    Year & Semester of completion: 2021 Semester 1

    Rating: 3.5/5

    Your Mark/Grade: TBA

    Pre-requisites: FNCE10002 - Principles of Finance

    Comments: Whilst this subject isn't actually directly needed for the finance major, it is needed as a pre-requisite to the major level 3 finance subjects, Investments and Derivatives. In addition, this subject used to be a level 3 subject back in the day.

    Lectures and content
    CFDM goes into the depths of how big corporations finance and what decisions they make regarding their financing decisions. This subject focuses on public companies (any company with stocks you can buy basically) so considering the recent trends, this subject is pretty useful!
     
    Lectures were just your typical finance lectures - pretty long (albeit they never exceeded 2 hours) and for the most part, pretty boring. Chander reads mostly off the slides but does add some important comments occasionally, so bear-the-boredom and watch the lectures! With that being said, he is a pretty cool guy and a lot better than the PoF lecturers.

    Let's talk about content: in twelve weeks, you'll learn about:
    Introduction & Options
    Spoiler
    You'll learn more about options as they pop-up somewhat frequently in this subject. Definitely not hard and this is the closest "PoF" type topic you'll get in this subject
    Raising Capital: Equity
    Spoiler
    You learn how companies issue stock to raise capital - whether that be through private or public means. There is a huge emphasis on public stocks here so don't worry too much about private placements - they'll only appear on the MST I think.
    Debt and leases
    Spoiler
    This time, you learn about companies taking on debt and leases/leasing to raise capital. This is the first tricky week of the subject, especially with the leases. However, it's relatively intuitive and after enough practice, it's not that bad.
    WACC and capital structure policy
    Spoiler
    Expands more about WACC (CAPM, debt etc.) and further elaborates on certain policies - irrelevance theorem, trade-off policy etc. Definitely a very theory heavy week so get your notes done as soon as possible! WACC calculations are simple and follow PoF with a few caveats.
    Payout policy
    Spoiler
    How companies pay dividends (if they even do). This is actually a tricky week if you're not careful - especially with tax rates. Read the slides very carefully as they will test you on this!! The timeliness of when you receive the dividend does affect a lot (capital gains tax, share prices etc.) I only remember this since my friend told me about this 30 minutes before the exam, and it popped up in a question! Shoutout to her!
    Mid-sem test/break
    Spoiler
    Pretty self-explanatory! Mid-sem assesses weeks 1-5. Good luck!
    Sensitivity analysis, break-even analysis and decision tree analysis
    Spoiler
    This is an interesting week actually - you'll mostly focus on decision-tree analysis since that's pretty doable (kind of like tree-diagrams you do for probability questions). Not a hard week, and to be honest I didn't watch the lecture this week.
    Real options
    Spoiler
    Options appear once again!  This time you learn how to emulate finance decisions via options - e.g. you can think of the potential to expand a business as a call option. This week also continues decision-tree analysis.
    Takeovers Part 1
    Spoiler
    You learn how companies takeover other companies. There's a lot of maths here but it isn't too bad. You learn that "1 + 1 > 2" here but it'll make more sense when you learn the concept of 'synergy'.
    Takeovers Pt. 2
    Spoiler
    More theory heavy this week, you learn other ways of taking over and how target companies can defend from hostile takeovers. You also dabble a little about how private equity firms use debt to buy-out a company here.
    Corporate restructuring
    Spoiler
    Learn how companies change their internal structure, why and how they do it! Not too much about this week from memory but still pretty important.
    Risk management
    Spoiler
    Essentially an introduction to the third year subjects - but without the maths components. Don't fret too much about this.

    Tutorials
    This was one of the many subjects that re-introduced in person tutorials. They were great - especially if your tutor was good. My tutor was great and could easily explain concepts that Chander/slides could not. Really recommend that you try to get an in-person tutorial (if you can). Definitely grateful that I went to all tutorials since the tutorial answers can be tricky, albeit the head tutor does upload his video solutions every week on LMS/Canvas. There is no hurdle requirement/participation mark here, so feel free to drop-out of tutorials. For the most part though, the tutors were nice and knew what they were talking about...

    With that being said, it seems like semester 2 2021 CFDM does have a 10% participation mark in tutorials - meaning a 70% weighted final exam. Not sure if this will be the case for future years.

    Assessments
    Both assessments were open-book and non-zoom supervised.

    The mid-semester test in this subject is tricky. It's not hard - you can easily answer all the questions (it's 20 MCQ), but the answers were very detailed and you really had to be on top of your game to get a good mark here. Answers would often have two phrases within them - for example, say the question was "What's 1+1?". One of the answer choices would be "1 + 1 is 2, but only if 2 is a negative number". Obviously the first part is correct, but the second phrase is false! Just imagine this in a finance context and you can see why this gets really tricky. This wasn't even the worst part - you always had "none of the above is true" or "more than one of the above is true" answer options to choose from. This meant even though one answer was obvious - you have to check for the others to see if it they were right. As such the average mark for this MST was 11/20, and it has been around this level historically. I don't think it gets better in level 3 subjects as I've heard haha. :(

    The 80% exam is a bit scary, but honestly I found it a lot easier than the MST. It features 20 MCQ (similar to MST in terms of difficulty and style), around 8 true/false questions (where you had to explain why as well - this was the bulk of the exam as it was worth 40 marks), and 3 short/long answer questions (which were almost all mathematical based). New edit: this exam was scaled by 17 marks! Wow!

    Chander only gave us one sample exam, which served us well. The questions were on par difficulty to the real exam, and the last question of both exams were similar. Still though, I couldn't get a sufficient answer here. You'll have to make sure you have a decent scanner/or use a tablet here, since Chander and the tutors only accepted handwritten answers. Make sure you upload early onto Gradescope!

    In terms of the content tested, Chander mentioned 60% of the exam would be on weeks 6 onwards, and 40% in the first half. He definitely lived up to that, so be prepared to check closely on notes from weeks 1 - 5. As this exam was open book, you didn't need to remember much, but having organised notes will help you immensely and is the sole crediting factor to (potentially!) my exam success. I also recommend making "cheat sheets" - notes on how to tackle problems with formulae.
     
    Concluding remarks
    Pretty interesting subject - if you want to do this as a breadth after PoF, then it's a departure from the formulas and more onto developing intuition and understanding the underlying theory about how companies work financially.

    P.S. I MESSED UP THE FORMATTING SO THIS [list LSIT TING] DOENST GO AWAY[/list][/list][/list]
    « Last Edit: July 01, 2021, 01:32:40 pm by dahyun »
    rip old forums... :(

    huy8668

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #827 on: June 24, 2021, 03:16:20 pm »
    +6
    Subject Code/Name: MAST90082 Mathematical Statistics 

    Faculty: Mathematics and Statistics

    Workload:  3 lectures a week and surprisingly no tutorials

    Assessment:  2 assignments worth 10% each and 1 exam worth 80%

    Lectopia Enabled:  Yes, with screen capture etc.

    Past exams available:  Yes, there was a mock exam which is a past exam

    Textbook Recommendation:  The course is based on the book Statistical Inference by Casella and Berger but you don't really need it. The lecture notes are self-contained.

    Lecturer(s): Liuhua Peng

    Year & Semester of completion: 2021

    Rating:  4.5 Out of 5

    Your Mark/Grade: Haven't received it yet

    Comments:

    This is a relatively relaxing subject at Master level and there is a legitimate reason for this: it is attempting to accommodate students from different backgrounds like say, Economics, Finance, Mathematics, etc. As a result, the rigour level is kept to a minimum and the pace is fair, meaning that the amount of content is also fair and that's what I meant by "relaxing" - relaxing in terms of amount of content, pace and abstractness. My view is that if you are someone who wants a chill subject, or a Maths students with interest in Statistics or a student from a different background wanting to do a Maths subject, you should definitely give this a go.

    To sum it up, this subject is, in my opinion, a sequel to MAST20005 Statistics in the sense that it revisits topics MAST20005 Statistics and explore them a little further but also doesn't go too deep in any topics. The "atmostphere" and "flavour" of the subject also resembles MAST20005 Statistics, not too much pressure (like say MAST20004 Probability or MAST30020 Probability for Inference).

    As for the content the subject is divided into 3 major parts

    1. Point estimators
    2. Hypothesis testing
    3. Interval estimators

    For topic 1,  the first 7 weeks, the set up is that we want to estimate certain quantities (say the average amount of money Australians make per day) and so we collect data and using those datas, we compute some figures. The questions one can ask are:
    • How should we compute these figures (What estimators to use? MME or MLE?)
    • What properties do these figures possess (Properties of MME and MLE)
    • How do we compare which figures are better? (Evaluating estimators)

    So the topics covered were
    - Method of moment and maximum likelihood estimators
    - Bias, mean square error
    - Uniformly minimal variance unbiased estimators (UMVUE)
    - Crame-Rao lower bound
    - Exponential family
    - Sufficiency, completeness and ancillary statistics
    - Rao-Blackwell and Lehmann-Scheffe Theorem
    - Decision theory and Bayes estimators
    - Asymptotic estimators

    For topic 2, the next 2 weeks or so, the set up is that we now have a claimed figure for our quantity of interest. Should we trust that figure? How can we test the claim? The natural questions one can ask (and thus, try to answer) are
    • Which tests are good?
    • Can we find a best test?
    The topics covered were
    - Uniformly most powerful test
    - Likelihood ratio test
    - Bayes test

    For topic 3, the set up is that although getting a figure for estimating our quantity of interest is nice, we don't know how sure we can be of such a figure. It might be instead nicer to get a range of values where we think our quantity lie in. But how do we find such an interval? How does changing the length of such an interval change our confidence level?
    The topics covered were
    - Inverting tests
    - Pivoting the CDF
    - Bayes intervals

    So the topics covered were more advanced than MAST20005 for sure, but the depth and rigor was kept low, which according to the lecturer, was kept low to accommodate students from various backgrounds.

    Lecturer
    The lecturer was great, knowledgeable and friendly guy, gave enough contact hours per week. It's also his fourth year teaching this subject so his exam and assignments were fair. There were some optional assignment questions, to challenge the students with stronger mathematical backgrounds. No complaints here

    There were no tutorials but I think it's ok because the lecturer went through many many examples in lecture for all concepts, which I quite liked.

    Overall, nothing peculiar about this subject. It was not too difficult, not too easy in terms of complexity and the amount of content was also fair. I'd highly recommend you guys taking this if you're looking for a doable subject. One still has to work hard for sure but for a master subject, it gives you a lot of breathing room. Definitely one of those subjects that the harder you work the better you do, almost linearly lol.

    Now that I think about it, I cannot really think of anything that was negative about this subject. If I was trying my best to knitpick, I'd say maybe considering how this is a theoretical statistics subject, I would've hoped that we covered a little more proofs and went through some deeper results in theoretical statistics. But then again, this is a general subject trying to accommodate a large population so I think it's optimum, the way it is now.
    « Last Edit: July 01, 2021, 04:22:57 pm by huy8668 »

    lm21074

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #828 on: June 26, 2021, 12:42:49 pm »
    +5
    Subject Code/Name: PSYC10003 – Mind, Brain and Behaviour 1  


    Workload: 2 x 1 hour lectures per week (for Learning and Cognition), 2 x 2 hour lectures per week (for Sensation and Perception and Behavioural Neuroscience – most lectures are split into two parts), 1 x 1 hour tute per week, plus research methods modules which overall takes around 2 hours

    Assessment: 1500 word essay – 40%, MCQ Exam – 55%, Research Experience Program participation or alternative task – 5%

    Lectopia Enabled:  Yes, with screen capture (lectures were pre-recorded)

    Past exams available:  Yes, practice quizzes were available for all of the components except RM (Learning and Cognition, Sensation and Perception, Behavioural Neuroscience)

    Textbook Recommendation: Recommended textbook readings are posted onto Canvas
    Lecturer(s): Learning and Cognition A/Prof Meredith McKague
    Sensation and Perception – A/Prof Piers Howe
    Behavioural Neuroscience – Prof Olivia Carter and Dr Jason Forte
    Research Methods - Dr Christopher Groot

    Year & Semester of completion: 2021, Sem 1

    Rating: 3.5 Out of 5

    Your Mark/Grade: results haven't come out yet but I know it won't be too good

    Comments: Overall, I really enjoyed this subject and found it was well-run. If you enjoyed psychology in high school or if you’re interested in the mind, the brain or behaviour, definitely give this one a go. A number of students in my tute were commerce students taking it as a breadth subject, but the majority were Sci/Arts/Biomed students. As mentioned above, the subject is split up into four components: Learning & Cognition, Sensation & Perception, Behavioural Neuroscience and Research Methods.

    L&C has some overlap with what is covered in VCE 3&4 Psych (e.g. classical and operant conditioning, memory and the amnesias). In S&P, you look at visual attention, motion, colour, depth, and object & scene perception as well as audition, which I found quite interesting. Behavioural Neuroscience, as expected, is quite biology based, and it goes into quite a bit of depth, but you will be eased into it. This content looked at anatomy and physiology of the brain and neurons and what happens when things go wrong in the brain. The Research Methods modules were a set of 12 videos run by Dr Christopher Groot, with recommended readings from a RM textbook (found on Canvas) and quizzes at the end. Each week, a lecturer did a Q&A session on whatever content was being covered. There were also discussion forums on Canvas for each topic covered.

    Tutorial content built upon what was learnt in the lectures and also focused on essay prep. The L&C tute content (conditioned compensatory response theory, etc.) was assessable on the exam. The RM tutes focused on using JASP and interpreting descriptive statistics.

    In Weeks 4 & 5, there were no lectures as we were guided through how to write an essay and the essay rubric and various assignment Q&A sessions were held. The assignment was a 1500 word essay on retrieval practice and we were given a lot of support with it. On Canvas, there were also assignment planning modules where you could plan components of your essay according to the rubric. One of the tutors ran Shut Up and Write Sessions over Zoom (which turned into Shut Up and Study Sessions once the assignment was over) which you can infer what they were according to the title. Really helpful for kicking procrastination.
    The exam was held in the last week of the exam period this year. It was an open book 120 MCQ exam (not sure if it would be open book if COVID wasn’t a thing), with 30 questions on each section. Some of the questions were the same as those found in the practice quizzes. Overall, I found the BN section the toughest and the RM section the best – an answer option for one of the RM questions was “OMG Chris, why are you being so mean to me?!”

    One tip I would give for this subject (which I guess goes for any subject lol) is to keep up with the lectures, especially the BN ones. Although you can get away with downloading the lecture slides and using control + F during exam, stress-watching heaps of lectures at a time before the exam really isn’t nice. Using solely the BN lecture slides in the exam isn’t the most helpful thing as some slides just contained pictures. 

    « Last Edit: June 26, 2021, 12:45:08 pm by lm21074 »
    2021: VCE
    2022: Science / Arts @ Monash

    ganksau

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #829 on: June 30, 2021, 11:32:23 am »
    +3
    Subject Code/Name: BCMB30012: Current Advances in Molecular Science 

    Workload: 1 module/week (total of 7 modules) with small video lectures, about 1h in total per week + 2 hour workshop/week

    Assessment: 3 written assignments (500 words each, 10% each) + 1 MCQ MST 10% + Group presentation at end of sem 15% + Paper review end of sem 15% + Final Exam 30% 

    Lectopia Enabled:  Yes, with screen capture

    Past exams available:  New subject, so no past exams.

    Textbook Recommendation: No textbook.

    Faculty: Science/MDHS

    Lecturer(s): Heather Verkade, Stuart Ralph, Malcolm McConville, Laura Edgington-Mitchell, Isabelle Rouiller, Ian van Driel, Paul Gooley (though they do change in Sem 2)

    Year & Semester of completion: 2021 Sem 1

    Rating:  4 Out of 5

    Your Mark/Grade: H1 (84)

    Comments: This was an okay subject, not my favourite ever, but didn't hate it either. This subject builds upon knowledge from lvl 2 BCMB to give us a "taste" of 7 research pathways we could go into: 1) Gene regulation 2) Epitranscriptomics 3) Metabolomics 4) Protein trafficking 5) Protein structure and function 6) CRISPR 7) Cell signalling and regulation.

    Each module is taken by a different lecturer (in order above). I found most of them to be really knowledgeable and easy to work with during the workshops. The lecture content is given in small videos (a la BCMB20002) and during the workshop you go through a research publication that applied the lecture content to obtain data and results, and discuss it as a group.

    This is a good subject if you're thinking of going into biomedical research, there's a heavy focus on publication writing, literature reviews and translational biochemistry.

    I found most modules to be okay, but because each were only 1 week long, they were often very vague. Module 3 and 5 were the absolute worst. 3 was just badly done, with no clear outcomes or what we're expected to know. The lectures for 5 were better, but the workshop was a waste of time, no discussion just us working through a question document while Isabelle was slowly scrolling through the answers... But the rest were all interesting and engaging, I highly recommend going in person if you get that possibility. I think Module 4 and 7 were my favourites.

    Overall, I didn't find this subject hard to do well in, the assignment guidelines were pretty vague, you'll have to write a Lit search review, a Ministerial Briefing and a News and Views article. If you've never heard of these before, neither did we. They were challenging to write because no one really knew what they were doing, but I think they were pretty lenient with the marking because I know lots of people got high H1s, including myself. The MST is mcq and I found it fair, but the average was around 65%, which I think balanced out the assignments a little. The presentation and paper review are based on the same research paper. You will be put in groups of 4-5 with a mentor, often an author on the paper and you'll have to present the paper to the rest of the class as a group and write an individual review, due at the end of semester. Everyone got an H1 on the presentation so again they were pretty lenient. And likewise, the review was pretty easy to write since, by then, you'd be pretty much an expert on this paper anyway. The final exam is saq, and like the MST, is based on the lecture content, so as long as you have decent notes, you should be right. A lot of people found it challenging, but I personally found it pretty fair. There werent any surprising questions and I think the time limit was decent.

    Finally, this is meant to be a sister subject for Advanced Techniques (BCMB30010) under the reworked BCMB major. While this made 30010 easier, taking both subjects concurrently was rough. Deadlines for both always in the same weeks, sometimes in the same day plus online practicals for one when we had in person workshops for the other on the same day (which sucks for someone with a long commute home). It felt like they did not coordinate these two subjects well together at all, so I would recommend taking them both in separate semesters. But maybe do this one first because you're taught how to do literature searches and all that which would be beneficial for the report in 30010.

    As a core subject for the BCMB major, its okay, really nothing to stress over, but you still need to put in some effort to get good grades, especially for the MST and Exam, but its really not that hard to keep up with the work, so it should be a fairly easy H1, especially as far as BCMB subjects go.
    « Last Edit: September 26, 2021, 05:25:49 pm by ganksau »
    2016-2018: IB (HL: Chemistry, Physics, English LAL. SL: Maths, Economics, Spanish B) 40 points
    2019-2022: BSci Unimelb (Biochemistry and Molecular Biology, H1)
    2022-2023: BSci Honours Unimelb (Biochemistry and Molecular Biology)

    Feel free to DM if you have any questions :)

    dahyun

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #830 on: July 01, 2021, 01:19:04 pm »
    +2
    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
    Spoiler
    This 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 directly
    Week 2 - Consumer preferences and budget constraints
    Spoiler
    This 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
    Spoiler
    Elaborates 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
    Spoiler
    A 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
    Spoiler
    This 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
    Spoiler
    By 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
    Spoiler
    After 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
    Spoiler
    It takes money to make stuff! Learn how producers minimise costs in a plethora of ways!
    Week 9 - Profit Maximisation
    Spoiler
    A 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
    Spoiler
    Learn 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
    Spoiler
    Learn 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
    Spoiler
    Whilst 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!


    rip old forums... :(

    Duckhole

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #831 on: July 02, 2021, 08:51:36 pm »
    +2
    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

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #832 on: July 03, 2021, 11:35:39 pm »
    +5
    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.



    2019-21: Bachelor of Arts (Politics & Int'l Relations / Economics)

    Tau

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #833 on: July 04, 2021, 09:43:16 pm »
    +2
    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.
    2020 - Bachelor of Science, The University of Melbourne

    2019: UMEP Mathematics Extension [First Class Honours (H1)], English [44], Specialist [42 ~ 52], Algorithmics (HESS)
    ATAR: 99.50
    2018: Physics [46 ~ 48], Methods [41 ~ 46]

    Tau

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #834 on: July 04, 2021, 09:57:46 pm »
    +1
    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).
    2020 - Bachelor of Science, The University of Melbourne

    2019: UMEP Mathematics Extension [First Class Honours (H1)], English [44], Specialist [42 ~ 52], Algorithmics (HESS)
    ATAR: 99.50
    2018: Physics [46 ~ 48], Methods [41 ~ 46]

    Tau

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #835 on: July 04, 2021, 10:22:50 pm »
    +2
    Subject Code/Name: MAST30021 Complex Analysis

    Workload:
    - 3 one-hour lectures
    - 1 one-hour tutorial

    Assessment:
    - 4 assignments (5% each)
    - Exam (80%)

    Past exams available:
    5 years worth from library, NO solutions.

    Textbook Recommendation:
    None, slides are sufficient.

    Lecturers: Dr Mario Kieburg

    Year & Semester of completion: 2021 Semester 1

    Rating: 3.5 out of 5

    Your Mark/Grade: H1

    Comments:

    Course Structure
    First 2 thirds of the course cover complex differentiable functions, continuity, holomorphicity, contour integrals, Cauchy's Theorems, deformations, Residue theorem, singularities, Taylor and Laurent series, logarithms and branch cuts, extended complex plane, sequences and series of functions... The last third is kind of a grab-bag of content including different applications with differential equations and harmonic functions, the Riemann zeta function, Beta function, analytic continuation, Mobius transforms.

    However, a significant amount of the course doesn't really seem to be examined or assessed on, and kinda seems a little incoherent in the flow - there is a LOT of content, and it feels like the subject could be streamlined to become more coherent.

    Note that there was no solutions provided to the tutorial sheets until very late in the semester (for complicated reasons), which was definitely a significant hurdle.

    My thoughts:
    Complex Analysis is undeniably an utterly beautiful subject. There is an insane amount of content, and it's absolutely incredible to learn. I found this way, way more interesting than Real Analysis, and it has massive connections to all areas of maths. Honestly, the proofs often made more sense to me than Real Analysis, and overall I was a LOT more engaged with the content (but still nowhere near enough). I definitely felt I gained a lot from this subject, and hope I've increased in my mathematical maturity and knowledge.

    However, I was not a very good student this semester, and spent almost no time per week outside of the lecture or tutorial practising or revising, and most of my 'learning' was in doing the assignments. This was definitely not a good approach, and I definitely wish I'd actually put more effort into the subject from the beginning. My preparation for the exam was a very superficial review of the content (too superficial), and working my way through the tutorials.

    Lectures
    Standard MAST lectures, however I didn't feel Mario so much 'explained' the content as told it to us. I felt this was definitely a let down, and part of the reason why I gave this 3.5/5 instead of. higher rating. Otherwise, the subject coordination was excellent, and Mario definitely cared about the students and was always very responsive on the Ed forum.

    Tutorials
    Tutorials were standard MAST tutes, definitely a highlight of my week. Andrei Ratiu is still IMO my favourite MAST lecturer/tutor, he's seriously knowledgeable, calm, polite, and has an incredible knack for explaining things perfectly.

    Assignments
    Assignments were HARD. There were 2 compulsory questions (often quite long with multiple parts), and 1 choice between a further computation or proof question. They took a lot of time to do well on, and you had to be really, really careful about each point. I managed to get 27/30 on 3, and 100% on my last one. I appreciated the opportunity to think properly about the subject content without the pressure of an exam, and I definitely learnt a lot from them. Mario introduced Assignment practice sessions after the second assignment where he would step through similar questions and show us how to solve them in detail, this was a life saver (Mario did the same for the final exam, so in many ways we knew what to expect in advance). The grade distribution was quite startling, with a large proportion failing on average. The exam was markedly easier in comparison. 

    Exam
    8 questions to complete, the last of which you have an option between 'Advanced Computation' or 'Advanced proof'. Mario was definitely very kind with the exam, the proof questions were definitely within reach and the computational questions were pretty straightforward. Honestly though, I'd kinda rather have had a harder exam, or one with more questions, since each one was worth a lot. There was no scaling this semester, and a markedly lower failure rate (19%). Be warned that each lecturer seems to set quite different exam/assignments and bring a different focus to the subject. Mario tried very hard to reduce the failure rate and make it more accessible.
    2020 - Bachelor of Science, The University of Melbourne

    2019: UMEP Mathematics Extension [First Class Honours (H1)], English [44], Specialist [42 ~ 52], Algorithmics (HESS)
    ATAR: 99.50
    2018: Physics [46 ~ 48], Methods [41 ~ 46]

    ganksau

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #836 on: July 04, 2021, 10:28:03 pm »
    +3
    Subject Code/Name: BCMB30010: Advanced Techniques in Molecular Science

    Workload: 1x 5h prac per week (no more lectures or tutes)

    Assessment: 30% Lab notebook maintenance, checked every week; 20% practical skills assessment; 15% Report draft components (5% intro, 2.5% methods, 2.5% results, 5% discussion); 20% Final Report; 15% final exam; HURDLE: completion of 2 worksheets, one at beginning of semester, one at the end and must achieve at least 70% in each to pass the hurdle

    Lectopia Enabled:  Yes, with screen capture

    Past exams available:  Yes, but the content has changed so not fully relevant anymore

    Textbook Recommendation:  None

    Lecturer(s): No lectures for this subject anymore, but Iza, the new coordinator will do some in-prac "tutorials" outlining the theory for some techniques

    Year & Semester of completion: Sem 1 2021

    Rating:  4.5 Out of 5

    Your Mark/Grade: H1 (87)

    Comments: I thought I'd write a review on this subject given that it's now been reworked to ease some of the workload. The presentation, for example, has now been transferred to the new sister subject BCMB30012. As mentioned above, there are also no more lectures or tutorials, only a 5h prac every week. There are 4 main experiments, all focusing on phosphatases:

    1) Transfect cells with phosphatase gene to express your enzyme
    2) Enzyme expression and activity assay
    3) Phosphatase localisation within the cell (microscopy)
    4) Mass spec

    Ex 1+2 will form the basis of your report and Ex 4 will teach you how to complete the 2nd hurdle worksheet. Ex 3 is really chill, and not really assessed, you just look at fluorescence under a microscope, pretty fun.

    The assessment has also changed a bit:

    Instead of having a 1-time draft for the report worth 15%, its now been split into 4 deadlines, each for one component. While this makes it easier to focus on one thing rather than get stressed about writing a full draft of the report in one sitting, this also means 4x the deadlines. And its critical to do well in the draft, so you can get feedback and write a good final draft of the report. However, 40% of the whole final draft will be an abstract and an appendix where you outlined how you incorporated the feedback from the draft into the final version. A lot of students, myself included felt a bit bamboozled by this because we did not get any feedback on any abstract and didn't know we had to write this appendix, so really only like 50% of you final report will actually be the draft components.

    The lab notebook is now 30% altogether, and you have to submit it every week, 2 days after your prac, and you should get a grade by your next prac. This will take you time. Don't underestimate how much time it will actually take you to complete the notebook every week. Some weeks it took 3 hours, others it took a whole day. DO NOT leave it until the last hour, you've been warned. When it comes to the marking, I'd quite subjective to each demo. I had Alex and was really happy, but I know others were stricter in certain aspects. It really depends on who you get as a demo and figuring out what they focus on and what they want to see on your notebook, and how.

    The 2 worksheets were before each graded at around 2-3%, and they've now been changed to a hurdle: you must deliver and get at least 70% on each to pass the subject. The first one is about using protein data bases and pubmed and really easy, you'd have to intentionally do bad to get anything under 80%. The second one is about Mass Spec and a lot harder if you're unfamiliar with it. You will go through most of it in class in the last 2-3 weeks, but make sure you pay attention and ask questions if you don't understand what's going on. I know someone that got exactly a 70% and im pretty sure its just because their demo was kind. This is such a stupid way to fail the subject, just make sure you dont miss the pracs on Experiment 4 and again, ask if you don't understand and you'll be right.

    Lets see what else? The exam is now 15% and given that there are no more lectures a lot of us were really confused as to what they could ask, but it was pretty chill. Half of it was calculations that you should have learned how to do in the pracs or year 2, and the other half was design an experiment (pretty easy) and a mass spec data analysis (again, experiment 4 is pretty important, make sure you pay attention).

    This subject is definitely easier than it was in previous years, but it still requires a lot of time commitment. The notebook and prac prep alone was half of my study for the whole week. It wasn't necessarily a hard subject, getting an h1 should be pretty easy, like nothing was particularly challenging, but it does depend on you putting in the time. It's a must subject for anyone looking to go into wet lab research and Iza is a great and really kind coordinator. Great subject, but I would highly recommend under loading if you're going to take it. I took 3 subjects and I struggled to keep up as it is, I can't imagine what it would have been like with 4...
    2016-2018: IB (HL: Chemistry, Physics, English LAL. SL: Maths, Economics, Spanish B) 40 points
    2019-2022: BSci Unimelb (Biochemistry and Molecular Biology, H1)
    2022-2023: BSci Honours Unimelb (Biochemistry and Molecular Biology)

    Feel free to DM if you have any questions :)

    Tau

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #837 on: July 05, 2021, 11:58:23 pm »
    +3
    Subject Code/Name: ECOM20001 Econometrics 1

    Workload:
    - pre-recorded lectures (~2 hours)
    - 1 one-hour tutorial

    Assessment:
    - 3 assignments (5% each)
    - Tutorial participation (5%)
    - weekly quizzes (1% each)
    - Exam (70%)

    Past exams available:
    Multiple+sample exam, all with solutions.

    Textbook Recommendation:
    Introduction to Econometrics by Stock & Watson. However, Dave's slides are excellent and plenty sufficient and I didn't ever use the textbook.

    Lecturers: A/Prof Dave Byrne

    Year & Semester of completion: 2021 Semester 1

    Rating: 5 out of 5

    Your Mark/Grade: 95 H1

    Comments:

    Course Structure
    The entire subject is basically one long introduction to Econometrics as a discipline, and to Linear regression via OLS as a foundational tool. You cover the basics of probability and statistics required for Ecom 1 (I guess a refresher for those who did QM1), followed by Single Linear regression, Multiple Linear regression, Non-linear regressions, interpretation of regression analyses, and time series regression (which is only very brief, but I found the most interesting). You learn about point and interval estimations and testing and interpretations, including p-values and confidence intervals.

    My thoughts:
    I came from a maths background (this was a breadth), so it definitely felt pretty chill since it's quite mathematical/analytical in nature. Really, there's very little foundations to this subject - 'Non-linear regression' is really just OLS applied to transformed variables (i.e. everything is linear in the parameters), time series is just regressing on 'lagged' values of the same data set, and multiple linear regression is just super-imposed linear regressions. Essentially everything you learn reduces down to the first 3 weeks of content or so, so just make sure you have a handle on that. I thought that everything was definitely useful to learn, but kinda wish I was able to do Econometrics 2+Time Series since I got bored pretty quickly and just felt I was lacking lots of depth. For commerce students, this subject will set you up really well for further studies. No regrets taking this, and definitely enjoyed the experience.

    Lectures
    Dave is an excellent lecturer and coordinator. The subject was incredibly well run, and just flowed seamlessly. Content is straightforward, the slides are excellent, just pause/take notes/ponder/whatever works for you and you should be fine.

    Tutorials
    Standard Commerce tutes, depending on the tutor you may find there's less or more interaction and explanation. My tutor, Sylvia, was excellent, and really made sure people interacted.

    Assignments
    Assignments were easy but quite tedious. You had the option of doing them in groups of up to 3, or individually. I managed to get 100% on 2/3, which is certainly possible with care and attention to detail. You're required to write basic R code, but no programming experience is expected. Weekly quizzes are easy marks, and a decent way to check your understanding.

    Exam
    The exam this semester was via Canvas (absolute pain typing in regression formulas this way), and was quite long. Many people found it harder than usual, and that they could not complete it in time. Exam questions are fairly standard, so just practice doing pst papers.
    2020 - Bachelor of Science, The University of Melbourne

    2019: UMEP Mathematics Extension [First Class Honours (H1)], English [44], Specialist [42 ~ 52], Algorithmics (HESS)
    ATAR: 99.50
    2018: Physics [46 ~ 48], Methods [41 ~ 46]

    tiredandstressed

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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #838 on: July 06, 2021, 06:34:14 pm »
    +4
    Subject Code/Name: PHYS30010 ADVANCED HUMAN PHYSIOLOGY 
    *new subject alert*
    Workload:  2 x 1 hour lectures, 1 x 1 hour workshop (however is in a lecture setting, NOT LIKE A TUTORIAL, but more interactive than a lecture)

    Assessment:  11 weekly individual online submissions: CAL (only 10 of the 11 tasks will count in final mark) (20%)
    *Basically 10 MCQ questions, some fill in the blanks and tick all that apply questions (open time & open notes, you have about a week to complete each quiz). Each quiz Is worth 2%
    11 weekly individual online submissions: Challenge Questions (only 10 of the 11 tasks will count in final mark, ~300 words) (40%). Each CQ is worth 4%.
    End of semester exam; which consists of 10 challenge questions, worth 100 marks. The exam was open for 24 hours however was expected to be completed within ‘two hours’. (40%)

    Lectopia Enabled:  Yes, with screen capture- Zoom lectures

    Past exams available:  No (new subject) but workbook questions are provided that were based of the exam

    Textbook Recommendation:  2nd year physiology textbooks might be helpful

    Lecturer(s):
    Spoiler
    L1: Central and autonomic regulation of visceral function I- Andrew Allen
    L2: Central and autonomic regulation of visceral function II- Andrew Allen
    WS 1: Central and autonomic regulation of visceral function- Andrew Allen
    L3: The heart – specialized structure and function- Lea Delbridge
    L4: Cardiac muscle cells & electro-mechanical coupling- Lea Delbridge
    WS 2: Cardiac Function- Lea Delbridge
    L5: Haemorrhage and shock- Charles Sevigny
    L6: Acute kidney injury and chronic kidney disease- Charles Sevigny
    WS 3: Renal function- Charles Sevigny
    L7: Erythropoiesis- Yossi Rathner
    L8: Haemostasis- Yossi Rathner
    WS 4: Blood- Yossi Rathner
    L9: Respiration I- Angelina Fong
    L10: Respiration II- Angelina Fong
    WS 5: Respiration- Angelina Fong
    L11: ENS and Endocrine I- Joel Bornstein
    L12: ENS and Endocrine II- Joel Bornstein
    WS 6: Digestion- Joel Bornstein
    L13: Inflammation I- Kristina Anevska
    L14: Inflammation II- Kristina Anevska
    WS 7: Inflammation- Kristina Anevska
    L15: Carbohydrate, fat, amino acid metabolism: the basics- Matt Watt
    L16: Fuel metabolism during exercise- Matt Watt
    WS 8: Metabolism- Matt Watt
    L17: Fuel metabolism and the adaptation to exercise training-- Matt Watt
    L18: The brain and metabolism- Garron Dodd
    WS 9: Metabolism II- Garron Dodd
    L19: The neuroendocrine adaption to metabolic challenges- Garron Dodd
    L20: The importance of skeletal muscle for health and longevity- Gordon Lynch
    WS 10: Muscle & Metabolism- Gordon Lynch
    L21: Regulation of muscle size: pathways of protein synthesis- Rene Koopman
    L22: Regulation of muscle size: pathways of protein breakdown- Rene Koopman
    WS 11: Muscle- Rene Koopman
    L23: Muscle development myogenesis- Kristy Swiderski
    L24: Skeletal muscle injury and repair- Garron Dodd

    Year & Semester of completion: 2021, Semester (completely online)

    Rating:  3.5 of 5

    Your Mark/Grade: H1 (88)   

    Comments:
    This is a new subject, and is now the new major core subject for the Physiology degree, but can be taken by other majors such as (HSF).
    Overall, this subject was intellectually stimulating, each week had a new topic which helped keep things fresh. Some topics were covered better, than others but otherwise was a good subject. The weekly challenge questions varied in difficulty but were a good task in assessing students knowledge.
    Lectures:
    2 x 1 hour lectures, means there is less content, than a usual science subject, which was nice. However, considering there is a weekly assignment question, it makes sense for there to be less lecture content. Lectures in third year focus on specific topics, that dig deeper from second year physiology. For example, in week 3 the theme is ‘renal function’ the lecture covered was haemorrhage and shock, so we are covering niche topics rather than a general overview which was presented in second year.
    Andrew’s lectures were standard, not overwhelming difficult however his challenge had little relevance to his lectures and was the first and most demanding question. Typically challenge questions were not expected to have further research (on diving adapatations) BEYOND lecture content but his did, his CAL was easy expect for one question, which again was not covered in detail in the lectures.
    Cardiac function delivered by Lea, covered the cardiac action potential and were delivered as small mini videos. I liked the content, and found it easy to understand, however some peers found her monotone, but she explains concepts with easy-to-read diagrams which was great. Her challenge question was arguably the easiest of the course, and was comparing two disease she covers when discussing malfunctions in the cardiac action potential)
    Charles takes us for renal function and focuses more on disease and pathogenesis, his workshop was helpful for the exam. His challenge question was a challenging clinical scenario that required a diagnosis, justification, and explanation of symptoms and why a certain treatment may be effective.
    Yossi covers lectures on blood, which was presented as interactive mini lectures, his slides were bare and he could unclear at times. His lecturing style was not appreciated by the cohort, since I felt his long explanations were unclear and incoherent. His challenge question was fair.
    Angelina covers respiratory physiology and again focuses on what causes respiration goes wrong, her lectures were wells structured and this was reflected in the CAL and challenge question, which was again another clinical scenario.
    Digestion… let’s just say the lectures weren’t that great. Slides were detailed which was good, but the presentation of the lectures were unengaging. However, what made it worse was the workshop! The workshop normally covers the CAL, the challenge question and student’s questions (if time permits). However, this workshop was so disorganised I left halfway because it was incomprehensible. Unsurprisingly, digestion was essentially omitted in the final exam (lol).
    Immunity was a repeat of second year immunity and didn’t focus on pathophysiology which was a bit sad, If you have done MCB, the immunity series will be very light for you.
    Metabolism and muscle were pretty straight forward and were covered well.

    Assessment:
    The CAL was a weekly 10 MCQ quiz, that covered the lecture content of that week, it was open for five days, untimed, open notes and open collaboration (yes you can collaborate in this subject completely, including the final exam)
    The challenge question was a weekly assignment-based question that required a short answer response of ~300 words that tested students abilities to apply their knowledge, no feedback is given to your individual response but an cohort feedback is provided. Averages ranged in the ~70%.
    The final exam was interesting, it was essentially 10 challenge questions, that covered all lectures taught in the subject. No practice exam is provided, but there were workbook questions, which is what the questions in the exam were based of. Two of the exam questions were identical to workbooks questions, and the rest required to content of those workbook questions but were adapted to be more of a clinical scenario. The exam was available for 24 hours but was suggested to be completed in 2 hours. This is a lie, majority of us took at least 8 hours to finish the 100-mark exam. This was because of the depth required in the questions, and ensuring your answer was simultaneously concise and detailed. The questions were fair, some were harder than others, but you have 24 hours to devour it. I assume the exam was marked relatively harshly considering it was only worth 40%. My advice for the exam is to answer all the workbook questions in sufficient detail and see if you can think of how a clinical example may arise from the provided questions.

    Overall, this subject was coordinated well, and the content was interesting and the assessment was rewarding and provided students with ability to be flexible in their learning due to the low-stake final exam. There wasn’t much support for student help which could have been improved.

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    2019-22: Bachelor of Biomedicine (Honours) @ UoM
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    Re: University of Melbourne - Subject Reviews & Ratings
    « Reply #839 on: July 17, 2021, 05:50:38 pm »
    +3
    Subject Code/Name: ECON30020 Mathematical Economics

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

    Assessment:
    5 assignments (individual) throughout the semester worth 10% each - your 4 best marks will be counted
    Final exam worth 60%

    Lectopia Enabled: Yes, with screen capture

    Past exams available: Yes, but the course was significantly changed in 2021.

    Textbook Recommendation: Mathematics for Economics, 3rd ed, Hoy et al

    Lecturer(s): Simon Loertscher

    Year & Semester of completion: 2021 Semester 1

    Rating: 0 out of 5 :(

    Your Mark/Grade: H1 (85)

    Comments

    Content-wise, the subject is split into three parts:
    - univariate calculus and optimisation
    - linear algebra
    - multivariate calculus

    I really wanted to like this subject. Despite my high hopes, it unfortunately ended up being my least enjoyable.

    Backstory - I did ECON20002 Intermediate Microeconomics in 2nd year with the legendary duo Svetlana Danilkina as my lecturer and Daniel Tiong as my tutor. They made me, an arts student with a horrific maths background (raw 34 in VCE Methods) become fascinated with the maths of economics. When Daniel suggested to me to do Maths Econ in 3rd year (which Svetlana taught and he also tutored for), I was doubtful as I barely passed high school maths, but I decided to go for it.

    Well, plot twist - a new coordinator came by the time I entered 3rd year. This subject ended up being a dumpster fire. The subject guide was released only about two weeks after the semester started, the Canvas page was horribly disorganised (lecture recordings were posted on the home page instead of under 'lecture capture'), and for some incomprehensible reason, Simon refused to annotate slides - instead, he wrote on spare pieces of paper, using a ballpoint pen that made markings his camera could barely pick up, and at the end of each lecture, posted photos of these scribbles for the rest of us to decipher.

    The only saving grace was Svetlana who uploaded her own notes (typed up, too, so that they were actually legible) each week, oversaw the discussion board and answered all questions. What I found amusing was that the subject coordinator actually put a disclaimer on Svetlana's notes saying that these are not official course notes. They certainly were much more helpful than the "official" ones he put up.

    Disorganised was honestly too mild of a word to describe it. Our first assignment was literally released an entire week late, and was actually only uploaded when multiple students emailed the lecturer or their tutor saying that they couldn't find it. When it was finally uploaded, it was actually Svetlana, not the subject coordinator, who made the announcement letting students know that the assignment was finally released.

    And if you think I am going a bit hard on this subject coordinator, I wasn't the only one with complaints. My tutorial size dropped from 21 students in the first week to only 3 by the census date. Yes - I repeat - THREE. Also, from reddit: https://www.reddit.com/r/unimelb/comments/lxj867/thoughts_on_econ30020_mathematical_economics_2021/

    For future students - only take this subject if the coordinator is Svetlana.
    2019-21: Bachelor of Arts (Politics & Int'l Relations / Economics)