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BuffInvestmentBanker :
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)

dahyun:
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
SpoilerYou'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
SpoilerYou 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
SpoilerThis 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
SpoilerExpands 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
SpoilerHow 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
SpoilerPretty self-explanatory! Mid-sem assesses weeks 1-5. Good luck! Sensitivity analysis, break-even analysis and decision tree analysis
SpoilerThis 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
SpoilerOptions 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
SpoilerYou 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
SpoilerMore 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
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. Risk management
SpoilerEssentially 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]

huy8668:
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.

lm21074:
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. 

ganksau:
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.

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