Worst unit ever. EVER. NO feedback for labs. NO preparation material for exams. WORST UNIT EVER. Has a mix of both coding and random content. It's such a mess. My friend dropped data science purely because of this unit. Lecturer needs to understand that students can't learn without feedback.

Ms Cara knows her stuff its just another useless irrelevant unit. I didnt learn python or anything I didnt already know from cits1401. And for some reason scared of making it production environment ready we just use jupyter notebooks. Each lab would take 3 hours to complete and all of them together make up 5% while the written exams you cant really prepare for are 70%.

Where do I even start. Its been the worst unit I've ever taken by far. Cara is an absolute joke of a lecturer. She cannot teach at all. She knows her stuff, but she doesn't know how to explain it to us properly, which is the whole point of a lecturer. This is pretty obvious with her lectures, with literally every second word being spoken by her being umm, errrr, ahhhh. She talks INCREDIBLY slowly, and pairing that with her not knowing how to explain things often means that the lectures get cut off by the recording system before she's even done "teaching". She does drawings on the whiteboard but doesnt have a camera set up so we can see what she's doing online, or she doesn't even provide us with any photos of what she's written. So some parts of the lectures are her explaining content to us with drawings etc while we stare at a black screen. In the last lecture, she talked about the final exam for 1.5 minutes. Yes. A minute an a half. While other lecturers would spend a whole lecture talking about the exam and going through exam questions or past exams, she gives no guidance at all. She just throws you in the deep end, and you have to teach yourself the content because she doesn't know how to. The way we would communicate with her is through Teams, and if there is a question she doesn't like, she simply won't answer it. What a joke. She told us the best way to study for the exam is to go through the lecture content and labs. However, the lectures were useless, and no answers were given for the labs. Multiple students asked for practice exams on teams, and it took her ages to finally produce us a one. Except that it was virtually useless. The ACTUAL exam mark allocations were 24 marks multiple answer MCQ’s, 30 marks coding and 6 marks short answer. The "practice exam" she gave us had the MCQ’s, but a lot of unnecessary short answer questions, and 0 practice coding questions. Very useful isn’t it considering 50% of the exam is literally coding, but she can’t be bothered providing us with any guidance or help on what those questions would be like. This caused the final exam to be very stressful and incredibly hard. This unit has really unmotivated me to do data science. It needs a complete 360, with a new lecturer and a whole new course structure. I don’t understand how the university has kept Cara for this long, considering the terrible reviews from past years, but they seem to be blatantly ignoring them. Her and the lab technicians don't care about the students, and they do the bare minimum, if that, with everything.

Most disorganised unit I have ever taken. 1) Started off the unit with no explanation of assessment/ lab weightage, so had no clue what to expect. 2) Lectures had no structure or learning objectives, so taking notes was difficult as nobody knew if we were meant to learn coding or random ethics about data representation. 3) Labs were difficult and while learning about new libraries (e.g. pandas, numpy, csv) were useful, no solutions were given despite everyone asking for them (which went completely ignored). 4) Vague instructions given for studying for exams - we were told to "look at our labs", but we never got any feedback or code solutions to learn from so we had to rely on our own wrong code. 5) Final exam was unnecessarily difficult - content tested did not at all reflect the skills we learnt and some questions focussed on a very small irrelevant section. We also had to hand write code, which is terribly unintuitive and is feedback for a lot of units, not just this one. Overall, this unit was the worst unit I've taken in the Data Science major so far and needs thorough improvement in delivery and structure.

Dropped out of this unit due to the terrible lectures which had very little focus on coding skills. Labs were difficult and answers were not given and the unit structure is very confusing. I was belittled for asking the weighting of certain assessments by lab facilitators as they were not clearly posted, was told to 'use my brain' and I would find them in the unit outline (news flash: they weren't in the unit outline.) CoCalc is a terrible platform for the labs. Dropped out of the Data Science major entirely because of this poorly organised unit.

Very challenging unit, the lecture content is political, heavily geared toward ethics, and doesn't focus on improving coding. Going to the labs is a waste of time, only vague answers to questions asked. There are no lab solutions posted, so theres no ability to learn from your mistakes. No previous years exams to study. The unit coordinator is well decorated and has substantial industry experience, however the unit was poorly organised. The end of year exam contained a large portion of techniques that we only briefly touched on, beware. It should also be noted that, all students should practice hand writing code throughout the semester, to be completely confident during the tests. Seems counterintuitive that one of the most prestigious and expensive universities in the state cant organise an examination via computer for a computer coding unit. Before taking this unit i would read 'Python for Data Analysis' by Wes McKinney if you want to do well. With consideration to the growth of Data Science as a career, this unit may need restructuring to incrementally build on industry standard coding techniques. This 1 star rating reflects the delivery, organisation of the unit and not the unit coordinator personally. The disconnect between the lectures, lab and exams is vast. Don't trust that if your completing labs and assignments that you'll have the required knowledge to ace the exams. Good luck.

It's really hard to learn Python all at once while trying to focus on all the assignments.

TLDR; If you want a good data science introduction, that is infinitely cheaper and infinitely more useful than this sorry excuse for a unit, read Python for Data Analysis by Wes McKinney (which is FREE) https://wesmckinney.com/book/ | The absolute worst data science unit this university has to offer (which in itself, is a bit of an accomplishment. Unit was run by Cara). The lectures are devoid of content, and equate to empty ramblings about politics and "why you should always be ethical when you do data science". I would download the lectures for the week just so I could watch them on 4x speed on the train, which did not impact my learning from the lectures (mainly because the useful notes would amount to a couple sentences from each lecture). A lot of the unit and projects focus on parsing in data by manually reading the text data (as opposed to using packages like pandas, which is the industry standard for reading in data). I have never had to manually parse in text data from a CSV in my professional data science career, and is a very low priority skill. I could say so much more about this unit, but its not worth my time and other reviews cover what I want to say.

The WORST and most UNORGANISED unit I've ever done. Would give 0 stars if I could. 1. LECTURES were mostly case studies that I would probably care more about if we actually learnt any useful programming from them. I understand the need to be aware of misrepresented data but ALL our assessments involve programming with Python and we were barely taught any. 2.WEEKLY LABS that were stupidly difficult. No clear learning outcome or guide, we were just thrown into the deep end to "figure it out". Spent hours and hours trying to complete them with no help from the lectures or lab facillitators (most of them uninterested and rude). 3. NO FEEDBACK was given for the weekly labs. NONE. You code, run the tests given and even if the tests work out you can still get it wrong. All the weekly labs were out of 3-5 points (1 point per question) so if you lost 2 marks in a lab that was out of 3, there you go, a 33% grade handed to you with absolutely no feedback on what or where went wrong. 4. NO PRACTICE QUESTIONS OR PAST PAPERS to study for anything! When asked for them, we were told that we should be studying from our weekly labs. Absolutely ridiculous! As far as I knew, everyone was struggling with the labs with most having very low averages. With no feedback on them, we had to study for the exam using our very flawed code which was full of errors and without any guidance. 5. FAILED MID-SEM EXAM due to poor organisation (waste of our time and effort to study for it). The mid-sem exam was done on CoCalc and I guess not enough testing or trials were done because everyone's paper were delivered at different times. Personally mine came through 35 minutes after the given start time. Cara sent out a message on Teams that the time starts after we have received our paper but not everyone had read it midst the panic so many had submitted it at the given end time even though they "started late". In the end, Cara decided to omit the mid-sem exam from the total unit mark and its weightage was added on to the final exam. 6. BREACH OF ACADEMIC INTEGRITY during the mid-sem exam. Cara had answered a question that was posted on teams while the mid-sem exam was in progress. She had made it crystal clear that "Students are not allowed to communicate with others (students or otherwise) during the test". 7. FINAL EXAM WORTH 68.5%. Not sure why the mid-sem's weightage couldn't be distributed among other assessments. 8. LACK OF RESPONSE from Cara. It was hard enough to get an email back from her and even harder to get a reply for a question posted on teams. Even weeks before the final exam, Cara rarely ever replied to any questions on teams.

Really poorly run unit (should be 0 stars/5). All in all I think I learned more by spending a couple of hours doing online Kaggle courses than I did in this unit. The first couple of weeks' lectures consisted primarily of going through news articles/Trump interviews pointing out times when data has been misrepresented. I honestly don't care about detecting false news, I picked this unit because I wanted to learn data science. I also emailed the lecturer on multiple occasions, requesting transparancy as to why I had lost marks in the labs. I had passed all the test cases and was confident in my code but would lose a couple of marks - these add up especially given the labs were scaled up after the midsem exam disaster. She replied to one email with some very abstract comment about not stripping out quotes - something I definitely did which is why I passed the test cases. Another email never got a reply.