Year 1 Semester 1

Hello! I am a Business Analytics student from School of Computing in NUS - I am actually an upcoming 4th year, but I have been writing my module reviews all over the different platforms, so I thought to consolidate all into one blog for easier reference. I will start from my first year, so bear with me as I slowly fill up the blog!

Modules Taken: BT1101, CS1010S, MA1102R, GER1000. IS1103, CFG1002

BT1101: Introduction to Business Analytics

Lecturers: Dr Sharon Tan and Mr Benedict The

Textbook: Business Analytics: Methods, Models and Decisions by James R. Evans (2nd edition)

Grading:

• Tutorial and Online Assignment (DataCamp): 20%
• Case Studies X 2 (Group of 3): 30%
• Practical Assessment: 20%
• Final Exam: 30%

Syllabus:

• Lecture 1: Course Introduction and Overview to Business Analytics
• Lecture 2 (Public Holiday): Self-Learning of R Programming in DataCamp
• Lecture 3: Implementation and Value Generation with Business Analytics
• Lecture 4: Data Visualisation
• Lecture 5: Descriptive Analytics through Descriptive Statistical Measures
• Lecture 6: Descriptive Analytics through Statistical Inference and Hypothesis Testing
• Lecture 7: Trendlines and Regression Analytsis
• Lecture 8: Forecasting Techniques
• Lecture 9: Data Mining
• Lecture 10: Monte Carlo
• Lecture 11: Linear Optimisation
• Lecture 12: Integer Optimisation

Exam Cheat Sheet: 1 A4 paper (double-sided)

Module Overview

This was easily one of my favourite module when I first matriculated into NUS! It is directly related to my major, and is my first exposure to data analytics. This module has exposed me to the different types of analytics that are commonly used in the industry - i.e. descriptive, predictive and prescriptive analytics. Even though the module can be very heavy in terms of its content (which is expected, and I do learn a lot from it), it also focuses on your R programming skills. In general, the lectures are heavily focused on theories, while the tutorials are heavily focused on coding in R for the different concepts. It is actually a fun module for me, but do expect this module to be tough as it can be hectic with weekly tutorials to be submitted as well as the two case assignments and minimal help is provided. I encourage you to approach your tutors and approach the UG TAs for consultations if you really need it.

Lecturers

Both Dr Sharon and Benedict are good lecturers who have planned their lessons ahead and are well-prepared for the lessons. However, Dr Sharon tends to overrun her time (also due to the immense content that she has to go through), and she ends up having to record the excess in her free time to be uploaded onto IVLE (before Luminus exists) for us to access and listen at our own time. For Benedict, it could be that the portion that he covers are much tougher, so I tend to get lost much easier and his explanation did not help as much. Textbooks and rereading the lecture notes multiple times were helpful though (and clarifying with the UG TAs)!

Final Grade: A-

CS1010S: Programming Methodology

Lecturer: Dr Zhou Lifeng (and Dr Leong Wai Kay)

Recitation Tutor: Adi Yoga

Grading:

• Coursemology: 25%
• Tutorial Participation: 5%
• Mid-Terms: 15%
• Practical Exam: 15%
• Final Exam: 40%

Syllabus:

• Lecture 1: Basics of Python
• Lecture 2: Functional Abstraction
• Lecture 3: Recursion, Iteration and Order of Growth
• Lecture 4: Higher Order Functions
• Lecture 5: Data Abstraction
• Lecture 6: Working with Sequences
• Lecture 7: Searching and Sorting
• Lecture 8: Implementing Data Structures
• Lecture 9: Generic Operations
• Lecture 10: Object-Orientated Programming
• Lecture 11: Memoization, Dynamic Programming and Exceptions
• Lecture 12: The Last Lecture

Exam Cheat Sheet: 1 A4 paper (double-sided)

Module Overview

This was a fun, but extremely heavy and scary module to take, and the workload is seemingly like equivalent to 3 or 4 modules. Also, the fact that this was my first semester makes it even harder to cope with the rigour of the module, and often, I find myself lost on what the lecturer is explaining. To do well for this module, it is important to be very consistent with your work - which means getting your tutorials completed, your missions done well and right (ensure that you get the full 25% for your Coursemology!) and checking in with your tutors (and/or attending the multiple consultations hosted) whenever you have trouble understanding any concepts from the lecture. The assignments are also meant to help you to improve your programming skill, so take them seriously, and do not simply copy/modify codes from your friends. They can be very difficult to manage, but as long as you push through this module, you are all set and well-prepared for any other modules in the future.

Lecturer

In this module, I was assigned to Dr Zhou Lifeng and I have stuck with him throughout - there was one lecture when I learnt from Dr Wai Kay though (as it is a make-up lecture due to the public holiday in week 2). In general, both are great at what they teach, though Dr Lifeng is much more succinct and to the point of what he teaches. i.e. He modifies Dr Wai Kay's slides by removing the "unimportant" elements. While I feel Dr Wai Kay is more energetic in his teaching, I prefer Dr Lifeng's teaching style, but it really boils down to individual preferences. 

Recitation Tutor

Adi Yoga is a great tutor, and is extremely clear in what he teaches - he is able to clarify any challenging concepts easily and makes the whole module much more understandable. It has been really pleasant learning from him in his recitation, and I really recommend learning from him, and asking him questions when you need to clarify concepts and/or approach. Since then, he has also finished his PhD and is now teaching modules as a lecturer, so do look out for his modules if you are keen!

Final Grade: B+

MA1102R: Calculus

Lecturer: Prof Goh Say Song (and Dr Wang Fei)

Textbook: Thomas' Calculus by G.B. Thomas, M.D Weir and J. Hass (16th edition)

Grading (Weightage cannot be recalled): 

• Mid-Terms
• Finals
• Assignments X 3

Syllabus:

• Chapter 0: Functions
• Chapter 1: Limits
• Chapter 2: Continuous Functions
• Chapter 3: Derivatives
• Chapter 4: Applications of Differentiation 
• Chapter 5: Inregrals
• Chapter 6: Transcendental Functions
• Chapter 7: Techniques of Integration
• Chapter 8: Applications of Integration
• Chapter 9: First-Order Differential Equations
• Chapter 10: Revision Lecture 

Exam Cheat Sheet: Not Allowed

Module Overview

This was an extremely challenging module for me, so do not be fooled by the innocent module name and the module syllabus. I regretted taking this module over the easier variant MA1521: Calculus for Computing, so I do not recommend you to take this module unless you really want to challenge yourself. I actually did not expect this to be so difficult, especially considering that I love (really really love) Math back in JC. If you do want to take on this challenge though, you need to be prepared to do a  lot of practice in tutorials and past year papers (which I obviously did not do). You will encounter a lot of proving in this course as well, which is something new and the proving is extremely rigourous actually. A lot of such questions will be found in the exams, as opposed to the usual computational questions you have seen previously. You are considered lucky if you encounter computational questions and even then, the questions are usually very complicated. A formula sheet, along with the common definitions/theorems, will also be provided - you will not be allowed to bring in a cheat sheet into the exams. Also, the assignments, while difficult, can be referenced with answers from the previous batches - there is only a very slight change in the questions, and the approaching to solving them pretty much remains the same.

Apart from the syllabus, you will also attend a lab session every alternate weeks, where you will learn a software "Maple", which helps you to compute the differentiation and integration of formulas, along with graphing them out. They are pretty interesting to learn, though I am already overflooded with R from BT1101 and Python from CS1010S, so I really am there to follow the commands provided in the worksheet. XD

Lecturer

I have taken the module under Prof Goh Say Song, and he is really a very bubbly and nice prof to learn under! It feels as though he is really bouncing around here and there in the lectures each time I see him. Also, since our assignments are submitted during lecture time, there are always some people who are doing last minute work, and he will be patiently waiting in the lecture hall after class to wait for everyone to complete their work before he leaves (sometimes waiting for over an hour). I am honoured to learn under him, and it has been fun with him around. However, he can be pretty old-schooled in the sense that he is still teaching by writing on OHP (which I have last seen back in my early Primary School days), but it is really dedication on his part to be writing everything live for us during lectures. Moreover, we have 2 lectures a week, and have lecture notes over hundreds of pages - just imagine how much he has to write each lesson! If you ever see a Math mod that he teaches (and that you are interested), just try to attend his lectures, and you will understand what I mean.

Final Grade: B- (S/U)

GER1000: Quantitative Reasoning

Lecturer: NIL (Uploaded Webcast)

Grading (from memory):

• Class Participation: 10%
  
• Weekly Quiz (Best 8 of 10): 20%
• Project: 35%
• Final Exam: 35% 

Syllabus:

• Chapter 1: Design
• Chapter 2: Association
• Chapter 3: Measurement
• Chapter 4: Sampling
• Chapter 5: More on Observational Studies
• Chapter 6: Uncertainty

Exam Cheat Sheet: Not Allowed

Module Overview

If you are a BZA major (looking at my blog), this module is very very manageable for you, with your statistics background. The concepts are easily understandable, but you need to ensure that you really understand every single detail for you to do well. Either way, you will learn these concepts again in your future statistics/BZA modules, so you might as well learn now and save you the trouble in the future. The questions in the exams are very tricky too, and the bell-curve for this module is very steep - any mistakes can cost you one grade. Do remember to secure as high as possible for your weekly quiz, and class participation!

The group project is a little more interesting, where you will be assigned to a group of 4 or 5 in your tutorial, and work on a project involving a news article to evaluate the strengths and weaknesses of it (i.e. critique it), which needs to be supported by the data provided. You will draw in all the knowledge and concepts you have learnt throughout this module. In the project, you are expected to deliver 2 presentations (1 proposal and 1 final), and 2-pages critique report.

Final Grade: A-

IS1103: IS Innovations in Organisations and Society

Lecturers: Dr Anand Mohan Ramchand and Dr Yang Lu

Grading:

• Assignment: 10%
• Weekly Quizzes: 30%
• Tutorial Participation: 25%
• Tutorial Submissions and Surveys: 10%
• Group Project (Open Letter): 20%
• Group Technology Presentation: 5%

Syllabus:

• Lecture 1: Introduction
• Lecture 2: Computing is Social
• Lecture 3: Ethical Thinking and Computing
• Lecture 4: Ethical Decision Making
• Lecture 5: Whistle Blowing
• Lecture 6: Ethical Decisions in Machines
• Lecture 7: Computing and Privacy
• Lecture 8: Freedom of Expression and Internet Censorship
• Lecture 9: Computing and Intellectual Property
• Lecture 10: Ethical Issues in System Development
• Lecture 11: Ethical Issues in System Development and Service Delivery
• Lecture 12: Ethical Issues in Artificial Intelligence

Module Overview

This is essentially a waste-time module and the module is poorly administered - with the grading all over the place, and the lectures and assignments not being organised well. There were barely anybody attending the live lecture as well, considering that the lectures do not actually value-add much to the knowledge (in addition to the webcast being uploaded). Apart from lectures, the assignments were uploaded extremely late (and the group project) - for example, the project should be given during recess week (according to the lecturer's schedule), but it was only given in week 10/11 of the semester, leaving us with very little time to complete. This is quite expected from Dr Anand, and his poor administration. The group technology presentation is extremely random as well, given that each group is assigned a very random topic in the tutorial (with mine talkin about blockchain), and having no relevance to ethics at all. It was a very disproportionate effort to secure that 5% as well. The tutorials were quite a mess, with the tutor not caring at all - he did not even once look up at us during the group presentation and he was just doing his own things (I was looking at his screen while other groups were presenting). The main group project, while relevant, was really not very helpful in ensuring that we understood the module's highlights and contents. Also, the group I have worked with was really questionable, so it made the project very eventful D: (e.g. different group members are typing in different font and font size, putting footnotes in the middle of 2 paragraphs, etc).

Overall, this module essentially focused on the different ethical frameworks and understanding them is critical to do well (and also meeting good group mates). 

Lecturers

Dr Anand was good at teaching and is dedicated to answer students' questions during lecture breaks and after lectures, so I got to say he was quite dedicated. He was able to explain his thought process well too - just that he cannot be doing the administrative side of the module. However, it is weird that he was doing these administration, when the module coordinator is actually Dr Yang Lu.

Dr Yang Lu is a really unique lecturer - while her accent is quite strong, she has that unique voice which makes me want to pay attention to what she is lecturing on (I usually attend the live lectures, but do my own work during lecture time). I can't help but to listen to her each time I sit into her lectures - which is quite useful when she teaches. She will be teaching the new BT2201: Business Concepts and Metrics for Analysis, so for the newly matriculated students, you will definitely see her around!

Final Grade: B- (S/U)

CFG1002: Career Catalyst

Grading:

• Resume Submission: 40%
• TalentConnect Profile (with values and career interests): 20%
• Video Recording of Elevator Pitch and Peer Reviews: 20%
• Professional Attire: 10%
• Lecture Attendance: 10%

Syllabus:

• Lecture 1: Career Planning
• Lecture 2: Effective Resume and Cover Letter Writing
• Lecture 3 (Recorded Video): Personal Branding
• Lecture 4: Interview Preparation
• Lecture 5: Networking
• Lecture 6 (Recorded Video): Excelling as an Intern

Module Overview

This is a very light, yet useful 2MCs module that can help you get prepared for your internship in future. The most useful and relevant knowledge I have gained for the module is to write out my resume, and have it vetted through by the careers advisors. Moving forward, I can easily edit my resume with new information, since the structure has already been established, making it very convenient for me. I would recommend this module if you love to build up your resume early in your University year, or is planning for an internship in your first year.

Final Grade: CS