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October 23, 2019, 02:59:43 am

Author Topic: UNSW Course Reviews  (Read 45145 times)  Share 

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kierisuizahn

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Re: UNSW Course Reviews
« Reply #150 on: September 17, 2019, 11:35:40 am »
+3

Subject Code/Name: COMP1531 - Software Engineering Fundamentals

Contact Hours: 2x 2hr Lecture, 1x 1hr Tutorial + 2hr Lab (Combined)

Assumed Knowledge:
Prerequisites:
Assessment:
  • 3% Quizzes - Three quizzes, each worth 1%; mostly just to make sure you're keeping up with the theory throughout the course; multiple choice with ten questions each; given a week to complete and submit, so very easy, especially if you look up the answers in the lecture slides or online
  • 12% Labs - A total of 7 labs weighted equally; some bonus marks in a few labs to make up for lost marks in others; mostly every week, but some weeks skipped for the project milestones; some of them were very long or required a lot of menial work, but none of them were particularly hard; submission at the end of the week they were released, and marked the same week or the following week by your tutor/lab assistant in person
  • 25% Project - A group project in groups of three (or four if your tutorial size requires it) from the same tutorial/lab; three milestones worth 10%, 30%, and 60% of the total mark of this component respectively; project changes every year, but ours was to create an online burger ordering system, similar to Macca's kiosks; first milestone was just user stories and acceptance criteria; second milestone was back end functionality of most of the features, plus documentation; third milestone was a complete backend and frontend, with documentation, and some bonus marks for extensions
  • 10% Midterm - Originally this was meant to be a 24 hour take home exam, but it became 48 hour because WebCMS went down near the submission deadline; out of 25, with 10 marks of multiple choice, and 15 marks in two diagrams made in draw.io; multiple choice was easy, but the diagrams were very hard to get looking pretty, considering how complicated they were; meant to time ourselves for 2 hours, but no one did, and the diagrams would have been very difficult to do well in 2 hours
  • 50% Final Exam - A 3 hour practical exam entirely on computer; out of 100, with 10 marks multiple choice, 30 marks short answer (some smaller programming questions as well), and 60 marks longer programming questions; first two parts were pretty easy, mostly testing how well you remembered the terminology and theory in the course, as well as writing test cases; last part had some more annoying questions involving refactoring and applying some basic OO design principles; as long as you knew the content there wasn't much challenge in the exam

Lecture Recordings? Yes - screen and voice recorded.

Notes/Materials Available: Lecture slides online. Tutorials and labs supplied with solutions online. Sample final and midterm exam provided.

Textbook: Note: I don't use textbooks and can't comment on their usefulness. None prescribed, but useful references:
  • [Recommended] Software Engineerings , by Ivan Marsic, Rutgers, The State University of New Jersey
  • [Recommended] Agile Software Development: Principles, Patterns and Practice , by Robert C Martin, Pearson

Lecturer(s): Aarthi Natarajan

Year & Term of completion: 2019 T1

Difficulty: 1/5

Overall Rating: 2/5

Your Mark/Grade: 94 HD

Comments: A dry course I didn't find much fun in, but with some useful techniques. The marking was very subjective, but a lot of the tutors were relaxed in marking because of it, which made it alright. The main language for this course was Python, but you were expected to mostly self-teach it, and there were some other languages that were required in the web dev part of the course (HTML, Flask, Jinja, CSS + JS if you wanted). The project I found particularly boring, and without good group members, would have been unbearable; The course staff were good, but the content they had to teach was way too boring for them to be able to make it an interesting course regardless. A lot of the content was rote learnt, which I really didn't like, and made summaries somewhat of a necessity for the revision; a lot of the content was simple, but there was so much of it that you needed to spend more time than I initially planned studying for it. No web dev was tested in the final, as it was a major part of the project, and was difficult to test in an exam environment. I wouldn't recommend this course to anyone unless you need to do it for your degree, or it's required for a course you really want to do. If you do do it though, be prepared for rote.

kierisuizahn

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Re: UNSW Course Reviews
« Reply #151 on: September 17, 2019, 11:36:49 am »
+3

Subject Code/Name: COMP3411 - Artificial Intelligence

Contact Hours: 1x 3hr Lecture, 1x 1hr Tutorial

Assumed Knowledge:
Prerequisites:
Assessment:
  • 40% Assignments - Three assignments, worth 12%, 12%, and 16% respectively; first assignment was a programming assignment in Prolog, which was easy if you understand functional or similar programming; second assignment was theory, running some search algorithms and comparing complexities, explaining why certain results occurred, etc.; third assignment was programming in whatever you wanted (main options provided were Java, C, and Prolog), making an AI to play ultimate tic-tac-toe; the supplied binary to test your AI against was really hard to beat, and in the end everyone's automarking marks had to be scaled up
  • 60% Final Exam - Two hour multiple choice exam, split into two parts; first part was only basic questions worth one mark, testing theory of the course; second part involved questions requiring calculations, and tested most of the computation taught in the course, and your understanding of those algorithms; because of the lack of past exams, it was difficult to prepare for the final exam, and a few of the more obscure topics were tested more than I'd hoped

Lecture Recordings? Yes - screen and voice recorded.

Notes/Materials Available: Notes on OpenLearning broken up into modules covering all the content. Lecture slides uploaded. Tutorial problems and solutions online. Sample final exam provided, but not in multiple choice format (from a previous session).

Textbook: Note: I don't use textbooks and can't comment on their usefulness. None prescribed, but useful references:
  • [Recommended] Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd Ed., Prentice Hall, 2010.
  • [Recommended] Ivan Bratko, Programming in Prolog for Artificial Intelligence, 4th Edition, Pearson, 2013.

Lecturer(s): Dr. Alan Blair

Year & Term of completion: 2019 T1

Difficulty: 3/5

Overall Rating: 3/5

Your Mark/Grade: 93 HD

Comments: This course was a pretty interesting course overall, but didn't go into enough depth. Instead, we covered a lot of topics very briefly, which ended up leaving me somewhat starved for depth. A good introduction to different parts of the broad topic that is AI, but not very interesting if you're looking to go into certain topics a lot, and requiring a fair bit of calculation. The multiple choice format for the final was for quicker marking (now that trimesters force it), and was pretty well executed, but the previous written exams seemed to suit the course a lot more, and allowed them to test your understanding of the content better, beyond just being able to calculate the required quantities. Dr. Blair was a somewhat dry lecturer, which made the lecture slides easier to go through, but the content on OpenLearning was sufficient anyway.

kierisuizahn

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Re: UNSW Course Reviews
« Reply #152 on: September 17, 2019, 11:37:49 am »
+3
Subject Code/Name: MATH3711 - Higher Algebra

Contact Hours: 2x 2hr, 1x 1hr Lecture (1hr lecture was basically a tutorial)

Assumed Knowledge:
Prerequisites:
  • MATH2601 or MATH2501, latter with at least a CR
  • 12 UoC of second-level maths courses with an average of at least 70

Assessment:
  • 15% Assignment - A typed assignment testing some of the more boring parts of the course; a lot more calculation-based than the rest of the course, with an extra conceptual question only for those in the postgraduate stream; pretty simple overall, with some nice tricks to cut down the amount of work you needed to do significantly, and marked for both correctness and presentation
  • 25% Midterm - A 30-minute exam taken during lectures; tested most of the first half of the course, about 50/50 proofs and theorem applications, with a few simple computations at the start; the biggest limiting factor was the time given to complete it, which was too short for the rigour expected in the proofs, in my opinion; the questions themselves weren't very difficult though
  • 60% Final Exam - A two hour written exam, with many proofs; tested the theory of the course very thoroughly, and required a good understanding of the content to perform well; there were a few difficult questions, which were marked leniently due to the time constraints; most of the questions were similar to the past papers, so it was pretty easy to prepare for the exam, with the supplied past exams alone; some of the harder (not time-consuming, just conceptually) tutorial problems were similar to questions in the exam, so doing those would have helped a lot in preparation

Lecture Recordings? No.

Notes/Materials Available: Lecture notes available online. Past final exams provided, some with solutions. Sample midterm provided with solutions. Problem sets with no solutions uploaded online.

Textbook: Note: I don't use textbooks and can't comment on their usefulness. None prescribed, but many references. See course outline for a list.

Lecturer(s): Dr. Mircea Voineagu

Year & Term of completion: 2019 T1

Difficulty: 4.5/5

Overall Rating: 4/5

Your Mark/Grade: 95 HD

Comments: I generally prefer analysis over algebra, but this course was actually really interesting. I probably would have enjoyed it more if it weren't examinable, as the timed assessments kind of sapped the joy out of doing the harder questions, but the course content itself was fun. It's easy to fall behind, since the pace of the course is quite fast, so I'd recommend keeping on top of things if you don't want to be cramming before the exam, and a few of the concepts are conceptually challenging, so having the lecturer explain them helped solidify my understanding. The lecture notes are mostly sufficient, but going to the lectures is recommended regardless.
« Last Edit: September 17, 2019, 12:19:49 pm by kierisuizahn »

kierisuizahn

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Re: UNSW Course Reviews
« Reply #153 on: September 17, 2019, 12:36:36 pm »
+3
Subject Code/Name: COMP2511 - Object-Oriented Design and Programming

Contact Hours: 2x 2hr Lecture, 1x 1hr Tutorial + 2hr Lab (Combined)

Assumed Knowledge:
Prerequisites:
Assessment:
  • 10% Labs - Weekly labs, with a break before a few of the project milestones were due; each lab was worth one or two marks (two if the next week's lab was skipped for a milestone), which added to 10 overall; marks were mostly as an incentive to do the labs, as some were similar to the programming questions on the final exam; other than the first lab (testing some git usage), they were all exclusively in Java; only a few of them were annoyingly long-winded, but most of them were very simple, and could be completed within an hour
  • 25% Project - A project done in pairs in the same tutorial group (threes if the tutorial size requires it); the best part of the course by far; this term was making a game given a specification; three milestones, worth 5, 8, and 12 marks respectively; first milestone was just user stories; second milestone was a completely functions backend of the game, documented and with tests; third milestone was the entire frontend coupled with the backend to make the whole game, documented, and with a couple of marks for extensions to the base specification; definitely not something you want to leave to last minute; a good partner would definitely help, but the project could be done alone if worst comes to worst, as long as you considered that contributing equally was assessed; incorrect usage of git could result in marks lost
  • 10% Assignment - A pretty basic assignment involving implementation of a booking system in Java; 6 marks for passing autotests, 3 marks for design (UML), and 1 mark for style (code style and tests); pretty easy task that could be done in a couple hours, but definitely more design-focused (even if the mark allocation says otherwise); straightforward if you know Java, or at least OOP well enough
  • 55% Final Exam - A three hour practical exam on computer; split into three sections, out of 100; first section was 20 marks, with easy multiple choice and some very short (1 sentence max) answers testing your ability to identify appropriate design patterns, some refactoring techniques, and understanding of OO concepts; second section was 30 marks, with some short response (2-3 sentences max) and smaller programming problems that were pretty easy overall; third section was worth 50 marks, and was just four programming questions; one was similar to the last lab (as we were told in the lab anyway), two were implementing given design patterns, and one was a refactoring task; the sample exam provided was a good indication of the kind of content in the final exam, and there wasn't much rote in the course overall, so the final exam wasn't difficult to prepare for, but definitely needed study

Lecture Recordings? Yes - screen and voice recorded.

Notes/Materials Available: Lecture slides all uploaded. Tutorials and labs with solutions posted. Sample final exam provided, with solutions.

Textbook: Note: I don't use textbooks and can't comment on their usefulness. None prescribed, but useful references:
  • [Recommended] Head First Design Patterns, by Elisabeth Freeman and Kathy Sierra, The State University of New Jersey
  • [Recommended] Refactoring: Improving the design of existing code, by Martin Fowler

Lecturer(s): Dr. Ashesh Mahidadia

Year & Term of completion: 2019 T1

Difficulty: 2/5

Overall Rating: 3.5/5

Your Mark/Grade: 99 HD

Comments: I was expecting a re-run of COMP1531, but was pleasantly surprised when there was actually very little rote. Most of the course teaches design patterns, which are easy to remember if you implement them, and some of the refactoring techniques require rote, but overall the course was mostly about identifying the benefits of the design patterns, and gaining experience in applying them so you could identify what pattern would be suitable for certain problems. The project was really fun, though that might be because we went over the top, but was the best part of the course in my opinion. The lecture slides were somewhat disconnected, which made revision difficult having not attended lectures, but after writing out a summary of everything and organising it, the course was very easy to study for; the concepts taught in the course are really useful, and I would recommend this to anyone considering working in industry. A little bit dry at times, but overall, pretty good.

kierisuizahn

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Re: UNSW Course Reviews
« Reply #154 on: September 17, 2019, 12:37:16 pm »
+3
Subject Code/Name: COMP9417 - Machine Learning and Data Mining

Contact Hours: 2x 2hr Lecture, 1x 1hr Tutorial

Assumed Knowledge:
Prerequisites:
Assessment:
  • 10% Homework - Two homework sets, worth 5% each; automarked, and involve selecting multiple choice solutions, or small snippets of output from programs; pretty basic questions to check how you're going with the course; supplied Jupyter notebooks with the relevant code (usually) done for you; mainly involve interpreting data and explaining why something happens (well, selecting which explanation is correct)
  • 30% Project - A large, term-long project in groups of 2-5 people (depending on the project); no tutorial restriction for groups; a list of available projects, as well as an option to choose your own project; approval from the course admin and lecturer required before commencing work on the project; what you do varies a lot with the project you choose, but all project need to have a report written up on them at the end, at approximately 2 pages per person, with a reasonably long appendix if required for large figures; marking criteria included marks for difficulty of the task to discourage choosing an easy topic for free marks
  • 60% Final Exam - A two hour multiple choice exam; see comments for a little rant; split into two sections, combined out of 120 marks; first section was questions worth a mark or two each (can't remember which) which didn't require much work, and mostly tested your knowledge on the theory in the course; the second section had variable-mark questions requiring a lot of calculation, varying from 1 mark to 12 marks each; generally testing your understanding of different algorithms taught in the course, and knowing how to apply them

Lecture Recordings? Yes - screen and voice recorded.

Notes/Materials Available: Lecture slides all uploaded. Tutorials and solutions uploaded. Sample final exam which didn't represent the final exam format at all also supplied.

Textbook: Note: I don't use textbooks and can't comment on their usefulness. None prescribed, and many references. See course outline for a list

Lecturer(s): Dr. Michael Bain

Year & Term of completion: 2019 T1

Difficulty: 3/5

Overall Rating: 3/5

Your Mark/Grade: 90 HD

Comments: The course content itself was pretty interesting, though the first half of the course was pretty dry if you'd already done a course on statistics. The last part of the course on learning theory is really interesting if you're looking into theoretical CS. The homework problems were really easy, and didn't represent the kinds of questions in the final at all, which made it difficult to gauge the difficulty of the final exam. The sample final was somewhat useful in that regard, but it would have been nice if it was in the same format as the final. The labs and tutes got kind of repetitive after a while, where I was spending more time interpreting the supplied Python code than I was actually doing the lab, but they did a good job of making me learn the ML packages we used for the project. Dr. Bain was a dry lecturer, but he explained concepts well in an intuitive and easy-to-understand manner.

Rant time. The final exam was trash. It really ruined the course for me. That 3/5 rating doesn't take the final exam int account else it'd be -5/5. The first part of the exam was fine, but when we got to the second part all hell broke loose. There were multiple corrections mid-exam. About 50% of the second part was literally impossible to answer (the multiple choice "answers" were incorrect; a few of my friends even resorted to rigorous proofs to make sure they weren't just being stupid to prove there was no correct answer), and there were questions worth up to 12 marks. In a 120 mark exam with 60% of the final mark for the course, that's 6% of your overall grade. I can't say whether there were partial marks or not, but I hope to god there was or that was the worst excuse for a multiple choice exam I've seen. I'd say there weren't but the course admin and lecturer were being incredibly cryptic after the course forum started going crazy as people complained. The amount of calculations required for some if the questions was ridiculous for a multiple choice exam, taking an entire page or more (note we had no working paper so we had to use the space between questions) to get one answer to one question, which didn't even have a correct answer. Even better, after all these issues were brought up to the course admin, they told us it would be marked fairly, and then never told us what they were going to do or how it was marked anyway. I still don't know how it was marked and I sent an email explicitly asking how (to which I got a non-response). The management of the final exam was horrendous. I hope it's never like this again.
« Last Edit: September 17, 2019, 12:38:53 pm by kierisuizahn »

kierisuizahn

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Re: UNSW Course Reviews
« Reply #155 on: September 17, 2019, 12:39:41 pm »
+4

Subject Code/Name: MATH3611 - Higher Analysis

Contact Hours: 2x 2hr, 1x 1hr Lecture (2nd hour of the last lecture of the week was basically a tutorial)

Assumed Knowledge:
Prerequisites:
  • MATH2111 or MATH2011, latter with at least a CR
  • 12 UoC of second-level maths courses with an average of at least 70

Assessment:
  • 20% Minor Assignments - Two written assignments submitted online and worth 10% each; covered recently taught content, and were mostly proof-based; some of the questions were based on the problems; marked for correctness, conciceness, and presentation; most of the questions were pretty easy; could be done in 1-2 pages; spent more time making my solutions concise than I did actually solving the problems, and didn't require too much abstract thinking
  • 20% Major Assignment - A large assignment with harder questions and more time; covered recent content, but that content was part of the harder topic in the course; required quite a bit of abstract thinking, and there were quite a few really cool shortcuts to the questions that weren't at all obvious; definitely not to be left until the last minute; could be done in 2 pages, so the solutions were more conceptually difficult, rather than long-winded
  • 60% Final Exam - A two hour written exam testing the course content in its entirety; the first two topics weren't taught much (as they were the focus of the minor assignments), but the rest of the content was tested pretty evenly; the format of the exam was pretty similar to the previous year's (being the same lecturer); definitely some challenging problems in the exam, and you need to know statements of some theorems well to apply them correctly; a sheet stating what parts of the course could be examined and which wouldn't be was released, which made study for the exam much easier; the past exams are very useful, as many questions are similar

Lecture Recordings? No.

Notes/Materials Available: Lecture notes uploaded, as well as solutions to the minor assignments. Problem sets with no solutions.

Textbook: Note: I don't use textbooks and can't comment on their usefulness.
  • [Prescribed] A.N. Kolmogorov and S.V. Fomin: Introductory Real Analysis (Dover, 1970; Call number: P517.5/125).
  • [Recommended] G.B. Folland: Analysis. Modern techniques and their applications.
  • [Recommended] W. Rudin: Principles of Mathematical Analysis
  • [Recommended] G.F. Simmons: Introduction to Topology and Modern Analysis

Lecturer(s): Dr. Pinhas Grossman

Year & Term of completion: 2019 T1

Difficulty: 4/5

Overall Rating: 5/5

Your Mark/Grade: 97 HD

Comments: My favourite maths course so far. I really love analysis, so that's sort of to be expected, but the proof were really fun, and the content was right up my alley. Dr. Grossman was a great lecturer, although we went an a few long tangents which dropped us a little bit behind schedule (they were interesting tangents though, to be fair). I would highly recommend this course to anyone interested in pure mathematics. Our class collectively wrote up some solutions to a few of the problem sets, though as the term progressed that kind of died; definitely helped when studying for the final though. A lot of the interesting exercises are in the lecture notes, rather than the problem sets. Not really much to say, just a good course all-round.