Module Review for AY16/17 SEM1

Overview of Modules

AY16/17
EG2401 Engineering Professionalism
IE3110 Simulation
IE4221 Transportation Demand Modeling and Economics
IE4243 Decision Analysis

**This review is based only on my personal opinions and experience.**

IE3110 is the last common ISE module to take. Following which all the remaining modules are technical electives.

EG2401 Engineering Professionalism
Here is a very good and rather recent review for this module. Very detailed coverage of each of the four parts of the module.

For the most part, the module was very light in workload. There is only 5 tutorials to attend including one for the project presentation. Some work has to be done before each tutorial and a report has to be submitted as part of the project. 

IE3110 Simulation

"This course introduces students to the basic concepts of discrete-event simulation systems and applying to problems that have no closed-form solutions. The course will cover modeling techniques, random number generators, discrete-event simulation approaches, simulated data analysis, simulation variance reduction techniques and state-of-the-art simulation software.

This course will enable students to analyze and develop simulation models of given problems."

This module covers most of the the content in the prescribed textbook "Discrete Event System Simulation" by Jerry Banks, up to chapter 11.

The first part of the module covers an introduction to simulation and some general concepts. With all the prerequisite modules, this part should be rather manageable. The second half of the module is more mathematical, focusing on the analysis involved in different steps of the simulation using statistical methods. Most of the statistics involved should be familiar, but there are some new content as well.

There are practices given in the form of tutorials and graded assignments and a project component. They are quite time intensive and requires heavy usage of excel. The software taught is Automod. There is some coding involved, but nothing too difficult. The software is not very simple to use as it is not fully programmable and there are many UI to familiarize to run a simulation model. Documentation is extremely poor and programs are tough to debug. Definitely a bad experience with the software.

Besides the workload for the graded components, the content itself is not too difficult because of the many statistical modules which have been taken previously or concurrently, notably IE2110 and IE3101. However, expect a harder curve for the grading as this module is worth 5MC.

IE4221 Transportation Demand Modeling and Economics

"This module introduces the basic economics concepts and principles as useful tools in the engineering context to formulate and analyze the decision-making of stakeholders (e.g. travelers, public sectors, shippers and operators). Special characteristics of transportation problems, such as the derived demand, mobile supply, cost structure, pricing mechanism and government intervention and regulation will be emphasized and some classic transportation models, such as user equilibrium model and discrete choice model, will be introduced."

There are three main parts to the module.

The first part of the module goes over economic theories and concepts such as demand and supply, market equilibrium and utility theory. The examples given are mostly from the transportation industry given the scope of the module. It should be straightforward if you have some economics background. The mathematical models covered should also be straightforward if you have some statistical knowledge.

The second part focuses on the cost structure of firms and pricing mechanism. The concepts mostly involve optimization and some mathematical derivations to obtain optimal cost and pricing. The third part involves on studying the combined effect of firms, buyers and government intervention and regulation on the transportation economics. Much of the analysis will be done using the supply and demand curve, this part is more analytical and less mathematical.

There is a project component on the module. It is basically a self directed research onto any transportation topic. Similar to any other ISE project. I didn't felt that there was any strong learning point on the project, and it felt rather burdening as the team numbers for this class is small and some of team members are quite competitive. 

Module Review for AY15/16 SEM2

Overview of Modules

AY15/16
IE2100 Probability Models with Applications
IE2130 Quality Engineering I
IE2150 Human Factors Engineering
CS2103 Software Engineering

**This review is based only on my personal opinions and experience.**

Took 3 ISE modules this semester, almost finished the entire set of common ISE modules. Also took CS2103 as a technical Elective. None of the ISE modules this semester are webcasted.


IE2100 Probability Models with Applications

Another very standard mathematical module. Main topics involve DTMC, Poisson processes, birth-death processes and queues. 

The topics are very analytical, but a lot of math is skipped in particular when deriving the models and some of the methods used for calculation. The topics tested are rather light and most of the difficult materials are not tested, making this module very manageable. 


IE2130 Quality Engineering I 

This module teaches the tools employed by quality engineers. The main topics are Quality Management, Control Charts, Process Capability Analysis and Acceptance Sampling.

The module does not demand very good statistics background as the statistical methods covered are quite basic and easy to understand. It is a rather interesting topic, and the module does not go to in-depth theoretically/conceptually and is more focused on applications.

IE2150 Human Factors Engineering

HFE is a collection of a huge number of topics. The module exposes to select topics involving human cognition and mental model, displays and controls, anthropology and human error. Research and observational study methods and practices were introduced at the beginning of the module. The topics chosen were sufficiently wide, you will most likely find a few topics of interest.

This module is one of the very few non-mathematical and analytical modules we have in ISE. I found it to be one of the more interesting modules. We also had to do a project to go through the design methodology. The approach for the project is rather focused on user experience. You can pretty much choose any topic to work on and then go and observe and interview users if you go out for it. I had a really fun group and topic which made the project interesting. 

Assessments are well distributed across the semester making no component especially heavy or light. Exams are writing based where you just need to either remember key concepts and principles and regurgitate them. Not a fun exam at all but at least you barely need to touch the calculator throughout the module. 

CS2103 Software Engineering

Reasons for taking this as my technical elective: 
At this stage, you are likely to have cleared all prerequisites for this module, making it easy to take this module in stage 2. This module used to be core for ISE, Software engineering is perhaps very commonly encountered in developing tech companies, and it is good to learn some software engineering practices as an ISE students since we are likely to work with software as well.

This module's information could be found online with a simple search, as the instructor posts a comprehensive teaching outline for the entire semester as the weeks goes by. In short, the module touched on introductory aspects of software design, implementation and testing practices. These knowledge are very useful in giving a glance to how software is developed. Interested students can pick up from here and work towards becoming a good software engineering. Many of my friends who have done the module have gone on to take up an internship in a software engineering role.

The module is taught primarily through a project component and lecture details. Both are useful and coming from ISE, I am glad to be exposed to the topic in such a structured manner with good selection of topics on my own. The module promotes self-learning and how much you learn is really dependent on time and effort put in. 

Software engineering is quite different from the algorithmic programming done in CS1020 and CS1010. It is also good general knowledge to understand the workflow and methods of how software is being developed.

Overview of Semester

Starting from the next semester, will be beginning to take ISE electives. There doesn't seem to be much choices though.

Workload is not particularly heavy in this semester, personally enjoyed the CS module and highly recommend it.

Module Review for AY15/16 SEM1

Overview of Modules

AY15/16
IE2101 Introduction to Systems Thinking
IE2110 Operations Research I
CS1020E Data Structures and Algorithms
ES2331 Communicating Engineering
IE3131 Engineering Statistics

**Disclaimer:
Any tips or personal opinions presented are based only and only on my personal experience.**

Took another 2 ISE modules this semester. Also with CS1020E, completed all the set of foundation modules for ISE. 

IE2101 Introduction to Systems Thinking

In this module we are exposed to systems thinking. It basically means trying to making a model to describe a real life system. Systems can be anything from Healthcare systems, transport systems, business supply chains to something smaller, basically anything. 

Basic modelling involves first drawing simple causal loop diagrams and stock flow diagrams, then trying to assign quantitative values to variables in the models. Afterwards testing the model and see if its a good representation, otherwise being a iterative process, repeat the process again.

We get to choose to create a model for any system we like. There are many interesting projects chosen and I have no idea how everyone goes about building their models. It feels like another project where things are done mostly for show and there isn't much learning going on.  

A very light and easy module (but may be hard to score - as with any ISE module), and where the project might take up a huge portion.

IE2110 Operations Research I

Introduction to Linear Programming and Optimization. Gives you a glance at OR and you could decide if it is your interest. The focus is on more problem solving and there is little focus on mathematical understanding. 

This module introduces us to linear programming, through a study of the famous simplex algorithm for solving linear constraint optimization problems. At the end of the course, some non-linear programming topics are introduced as well. The approach taken is rather application or problem solving based, and the focus is to teach how to solve problems.

This module also introduces algorithms to solve certain network problems. Taking Cs1020E concurrently can be helpful as you can also look at the optimization problems from a computer science perspective, and have a sense of how the algorithms can be possibly implemented.

The algorithms are not difficult and it is simple to apply the algorithms taught as they are similar to step by step instructions. Trying to understand and learn the math and theory behind the topics and algorithms is hard. However, it is not required and unnecessary to score, since the module only asks for problem solving.

Topics:
Simplex Algorithm
Duality
Network Models and algorithms
Convex Programming
Lagrange Multipliers and KKT

CS1020E Data Structures and Algorithms

Part two of the programming course. In this course, there will be a switch to C++. This should not be a concern if you have done programming in C as they are rather similar. This course is essential in introducing various programming concepts. Knowledge of these topics are really important to continue with programming. With what is learnt from this course, you can develop confidence and ability to self learn various topics that are of interests. Personally I do not think that lectures added too much value other than content, but it was much easier to follow the lectures rather than learn through reading. 

Most of the learning still comes from practice as it helps to cement the concepts. Heavy focus on implementation initially, but later on there will be exposure to abstraction and less focus on implementation at the most basic level and more on algorithms. Personally had a bad time with the topics before mid term, as they are very detail oriented and requires some strong coding skills to deal with OOP and the implementation details of linked lists. In the later topics the focus is less on programming and more on design and analysis of algorithms and the data structures.

Topics:
Programming in C++
OOP
Array and List
Stack and Queue
Hashing
Sorting Algorithms

ES2331 Communicating Engineering

English Module catered to engineering. Provide some opportunity to develop your communication skills further, not too useful other than the opportunity to practice.  Don't really have a choice here if you are an engineering student :) Get over and be done with it.
Got an average B+ for this module.

IE3101 Engineering Statistics

Topics: Review of Statistics and Probability
ANOVA
Regression
Design of Experiments
Not Covered: Statistical Process Control (Chapter 8)

The module follows the textbook Engineering Statistics by Montgomery closely. The first part was a review of everything you have learnt in 1131 and 2131. It gets interesting in the second part when the three main topics are covered. Prof Goh provides very useful interpretation on the materials. From the textbook, it describes very well how the statistical techniques taught are applied to engineering. There is little mathematical detail involved and the focus is on understanding and making correct statistical inferences and probably the only course where all the examples used are engineering examples. Allows you to appreciate the some of the tools taught. 

The module and topics are presented in a high level overview style. Many topics are covered and it can be really difficult to appreciate all the concept taught without any personal experience or opportunity for hands on application. It leaves you with alot more knowledge on statistical applications but does not build up your statistical foundations. Provides a good gauge of whether you have interest in statistics. 

Recommended to go for lectures especially for second part. Read the textbook as much as possible and look up things which you do not really understand as the book gives a quick introduction to too many topics without being able to explain in depth. 

Finally I got B. Exam was surprisingly difficult. I thought I had done ample preparation but I found it very difficult to answer the questions. There was little calculation involved and the focus is heavily on applications to engineering and on explaining some of the concepts clearly.

Overview of Semester
This semester exposed me to some higher level technical modules, which made me realize areas which I have had to learn more, especially probability and statistics and linear algebra. I am also becoming more interested in studying technical modules which I had previously thought I would not enjoy.

Module Review for AY14/15

Overview of Modules

AY14/15 SEM 1
MA1505 Mathematics I
ST1131 Introduction to Statistics
CS1010E Programming Methodology
GEK1549 Critical Thinking and Writing
EG1108 Electrical Engineering

AY14/15 SEM 2
MA1506 Mathematics II
ST2131 Probability
IE2140 Engineering Economy

**Disclaimer:
Any tips or personal opinions presented are based only and only on my personal experience. **

Introduction

This review is for the first year in the ISE course. This module review was done after Year 1.

MA1505 Mathematics I - 4MC
MA1506 Mathematics II - 4MC

Two Semesters of engineering mathematics modules where important mathematical tools for solving engineering problems are covered. The modules will equip you with the necessary understanding of how to use the various tools to solve problems. Strong focus on problem solving. Understanding and appreciation of the mathematical concepts is barely covered.


Ok, honestly these MA modules aren't very useful for ISE. Consider it training to improve your math skills rather. You can consider these engineering math modules more of a breadth, but do pay a little more attention to these topics:

• Linear Algebra
• Multivariate Calculus 
• Lagrange Multipliers

Content is rather heavy. Rather difficult to score. For both semesters, couldn't solve some of the questions in finals. Others were done wrongly due to neglect. I didn't perform too well under timed constraints as I practiced at a more leisure pace, but still manage to get the job done decently.

ST1131 Introduction to Statistics - 4MC

Topics covered are mostly covered under statistics syllabus of H2 mathematics. There is more focus on understanding than calculations. Content is moderate but the module itself is not intensive at all, especially for JC students. Somehow one of my favorite module of the first semester. I went for almost all lectures as there is no webcast. Most important is to grasp the concepts and understand the "why" behind the calculations. Pay some attention to this module despite its "lightness", it is good to have a strong foundation. You also get to learn about Minitab software, which is probably the easiest to use statistical software.

Takeaways:

• Inferences on up to Two Samples
• Intro to Sampling Distributions

Rather light and easy module. The bell curve can be quite skewed so it is really important to have correct intuition and understanding of the materials. There is ample time during the exam, to come up with the correct interpretation and demonstrate understanding of the materials, so make sure you are prepared to do it. This should not be a too difficult module as long as you are careful during the exams.

CS1010E Programming Methodology - 4MC

A fun module if you have not done programming before, and rather slow if you have. Basic introduction to programming in C. Most important is the logic of your code and developing good programming practices. When practicing develop good debugging practices to save time.

2 kinds of labs, one per week, alternating between graded and practice. During labs time constraint is really a problem as it can be insufficient hard to implement code even if you know how to do it. 

What I learnt:

• C Language
• Arrays and Pointers

Weekly Workload: Can take 8-15+ hrs if you plan to complete all the exercises and haven't done much programming previously.

GEK1549 Critical Thinking and Writing - 4MC

This is a writing module where you have to write a paper and report before an exam. Topics are generally restricted to engineering ideas/solutions. The paper was on critic-ting an article. Report is on presenting solutions to a problem. Exam format somewhat similar to GP. 

This module is quite difficult to score. I had spent quite a bit of time and thought I was writing quite decently, until the results got back to me. Maybe I wasn't writing what they were looking out for, so I can't offer any useful tips. What I got: B+

Review:
Was a good chance to learn to speak up in class but did not utilize it
Spend more time reading my individual paper, get more feedback 
Start reading more stuff!

EG1108 Electrical Engineering - 3MC

Really a light module with little content although it takes some time to familiarize with the content and problem solving. Works like an introduction to electrical components simple circuit diagrams. 

I took this to clear the requirements for ISE and also because it fits into th 23MC limit of the first semester. The module focuses on problem solving, so as long as you know how to do the questions, it should be fine. My style for the module is consistency, it should get you there will minimal effort:

• Recommend to go for lectures
• Go for tutorials if necessary
• Revise your mathematics if necessary
• Work consistently as it takes time to familiarize 
• Work through some past year questions 

The module can be seen more as a breadth module, it good to have the relevant understanding, especially if you are going to work on projects involving electrical engineering in future/with peers from electrical engineering.

Content is light, but I took some time to grasp the intuition behind them. After that, it is mainly mathematics. Have fun during the labs, I haven't got the chance to do something hands-on for a long time in a real lab since.

ST2131 Probability - 4MC

Heard that this module was rather difficult . Very mathematical and theoretical, involving the study of distribution functions in some detail, along with study of expectation and variance in some detail as well. The module also extends all the materials to multivariate distribution functions and bringing in concepts of independence and correlation. Content for the module is rather heavy. Didn't have time to internalize much of the materials towards the end and ending up just plugging formulas for the later topics.

There were several lecturers and all the lectures were webcast-ed. Try to have a feel of how each lecturer teaches and then follow the one you prefer most.

Webcast lectures at your own pace/You can self study if you prefer the textbook to notes. 
Do tutorial questions
Attend tutorials if necessary
Consistent studying and occasional revision during the semester is good as it takes time to absorb the content

Topics(topics gets harder and the pace tends to get faster as the lecturers probably had bad pacing at the start):

• Probability
• Random Variables
• Distribution Functions
• Multivariate Distribution Functions
• Expectation and Variance
• Moment Generating Functions is covered lightly but not tested

The final paper for the semester was as easy as it could have been, with just one difficult question while really blew my mind figuring out in vain how to solve. (for the A+ students probably). 

IE2140 Engineering Economy - 4MC

This is the first ISE module that I have taken and I had high expectations for it. In fact it turned out to be a "mix" of 50% finance, 20% probability, 10% accounting and 20% economics but with focus on engineering applications. To sum up the module, it is based on decision making based on NPV and cash flows. Content of the module is very light compared to all the engineering mathematics and your probability module. Expect to see content from your probability module appearing. 

There was a project component which involves analyzing a topic/situation using cash flow projection and recommending a decision. The topic is very broad and can be anything you deem doable. Personally I find that the project is very hypothetical and not realistic. There is insufficient information for the project to be meaningful. Recommendations could be to choose a really good topic/situation to analyse. There as a presentation at the end and the only feedback received was during the q&a. 

Lecturers likes to give question examples on everything covered. Some are really unnecessary and can be skipped while on webcast.  Homework involves some excel work and can be interesting. Use the build in functions to solve your tutorial questions if you do not want to work through the details.

Content is moderately heavy. Suprisingly hard to do well and score.

Review:
I had not done particularly well for the midterms, yet content of this module was mostly concepts I had knew before hand. As I did not see much learning value in something I had learnt, I did not take on the mid term result to prepare much for finals. I also had not put in too much effort for both the project and module. It is important to maintain a positive attitude for your projects at all times. There is also a need to get feedback more frequently during the project if you want to learn from it. 
Key learning point from this module is positive attitude for learning and project and humility.

Overall Review of Academic Year

I offer a little personal experience and advice throughout this review as I think most readers of this review will be from pre-univeristy.

Studying time and effort: a manageable year with good time management and consistency. 

Webcast is king: I converted to almost fully webcast during semester two, as I felt it was a more efficient way where you are in charge of the pace. Going to lectures also leaves you distracted easily, especially if you are there with friends.

Learning: Use semester one to experiment your learning style as semester two is likely similar. Both semesters have very technical foundation modules so your most effective learning habits from first semester could be applied directly over.

Mindset: Importance is to adapt quickly to the changing requirements, especially to the project environment and breadth modules during semester two.

Practical comments: Grade free semester is probably the easiest to score, since everyone around can S/U. Be sure to research thoroughly what modules you are likely to take so you can clear the appropriate prerequisites along the way (although things always change along the way)