FIT1043 Introduction to Data Science notes, batch of Semester 2, 2018.
notes is written by me. Do take note of any inaccuracies made by me.
Took this unit during my entry first semester. Much of what was taught in lectures were all about scraping data from online public datasets site like Kaggle. Speaking from the perspective of a person with no absolute background in "data field", this unit is considered as challenging for me, because much of the mathematical understanding behind the data modelling requires advanced mathematics skills such as Regression Analysis, Linear Regression.
So it was regarded as a "course without deep understanding". Assignments were easy and basic, which extracts info from the lecture slides and tutorials. Full marks are easily achievable as the assignments were opinion/analysis-based, where answers that make sense/valid/logic will be deemed to be correct, so there are no absolute answers in this unit, but like a philosophical approach of describing the data. Memorization constitutes a large portion of the exam, as the real understanding is not within the scope of the unit, so lots of stuffs are preliminary, which requires memorization. All-in-all, data science is statistics, without statistics skills, one could hardly understand the reasons behind data science. Would recommend this to people with interest in statistics, as it serves an elementary idea of what data is all about. It is also strongly and closely related to machine learning and artificial intelligence field.
Overall Rating: 2/10
Final Grade: HD
Copyright (c) 2019 Jun Qing Lim
The content of this repository is licensed under MIT License. See LICENSE for more information.