DISCLAIMER: firstly, i am not a professional writer, so if there are mistakes in my language, move on. secondly, the review is mostly based on opinions, so i would advise you to google for more reviews to get a diverse take on the modules you are interested in. thirdly, module details change every semester, so do not expect every assessment will stick. last but not the least, i will not talk about grades. hope this is useful for you, cheers.
what do you learn?
this module is one of the modules Statistics major students get to choose to take or not. it is not a compulsory level 4000 core module. through this course, one will be exposed to statistical techniques so as to analyse big data and pick out possible trends/relationships amongst the little mess. one will be exposed to techniques such as decision tress, random forest, classification and Ridge/LASSO regression.
assessments?
assessments vary quite a bit from lecturer to lecturer. for mine, we were graded on 3 group assignments, midterms and finals.
my personal opinion?
i find this module very interesting though it can be really challenging now and then. the group assignments are relatively easy to understand but time taken can be disproportionate to the weightage of the assessment.. lol. of the 3 group assignments, one includes a Kaggle competition among your coursemates. i suggest one to start early on this. content is alright when it comes to understanding but applying can be rather challenging. the exams are challenging for sure.. do not feel too discouraged if you cannot do like half of the paper. practise tutorial questions and be really familiar with the style and methods used in preparation for the exams.
click here to see the modules i have read and their respective reviews. do feel free to contact me via Telegram @alvinngjh for any questions or what not.
No comments:
Post a Comment