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CS2020
Data Structures and Algorithms (Accelerated)
2014/2015, Semester 2
School of Computing (Computer Science)
Modular Credits: 6
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Learning Outcomes
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Overview
: CS2020
is an accelerated course that provides a comprehensive introduction to algorithms and data structures. It is intended as a continuation of CS1010/CS1101s, combining CS1020 and CS2010 into a single fast-paced semester.
Focus
: The module will focus on the basic data structures and algorithms that lie at the core of computer science, and how they can be used to improve performance in real-world problems. Throughout the module, we will discuss how to model problems in different ways, and how differing strategies can yield very different performance characteristics. We will both analyze algorithms to better understand their asymptotic performance, and implement them in Java to understand the issues that arise in practice. The goal of this module is both to help you learn how to how to choose and use better data structures.
Organization
: The module is divided into 5 segments:
Arrays and linear data structures
Sorting and trees
Hash tables
Graph algorithms
Dynamic programming and other advanced material
Object-Oriented Programming
: Throughout, there will be a focus on object-oriented programming and Java programming. We will discuss how to formulate and model a problem in an object-oriented manner, focusing on basic principles of abstraction and encapsulation. We will also discuss implementation issues, including designing class hierarchies and error handling (i.e., exceptions).
Workload
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Summary:
4-2-2-4-3
Type
Time/week
Schedule
Lecture
:4
4 hours
Wed & Fri 10am-12pm
Tutorial
:2
1 hour
Friday (TBA)
Discussion Groups
:2
2 hours
TBA
Assignments
:5
5 hours
Weekly
Study time
:3
3 hours
Assessment
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Tentative Weights (6 MC):
Type
Date
Weight
Quiz 1
TBA
TBA
Coding Quiz
TBA
TBA
Quiz 2
TBA
TBA
Problem Sets (9-10)
TBA
Discussion Groups / Participation
TBA
Final Exam (in reading week)
TBA
Total
100%
Our policy is to work as hard as we can to give each student the final grade that they earn, and this will be the guiding principle behind the final grade assignment.
Prerequisites
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Obtain a grade of at least A- in either CS1010 or CS1101S.
If you did not secure a slot in the class via MPE, please e-mail your application to me answering (in no more than 5 sentences):
(0) Subject of the e-mail: "CS2020 Application"
(1) Your name and matric number
(2) Which class did you take to meet the prereq (cs1010 or cs1101s) and what grade did you get?
(3) Are you a student in SoC? If not, do you have a minor in CS?
(4) Is there any other special reason that you should be accepted to cs2020?
Preclusions
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CG1102, CG1103, CS1020, CS1020E, CS2010, CS1102, CS1102C, CS1102S
Advice from previous students
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At the end of every year, I asked students to provide advice for future CS2020 students. Here is a selection of prior responses:
Many students recommend it:
If you qualify for CS2020, definitely take it! [...] CS2020 makes you think about how to solve a problem in a manner you think that's best. No fixed answers, loads of flexiblity, great for learning.
If you like challenge, you should take it.
Work hard and enjoy the problems!
Take CS2020. Or die. xD
Students warn that CS2020 is hard:
Pain guaranteed, Fun too. Time Sink if you cannot draw away from fun stuff.
Try to work as hard as you can.
Make sure you can pick up concepts quickly.
Take it if you have the time to learn on your own [...]
[Give] a warning at the start of the module [that] things are gonna be really tough, and that students have until week x to decide whether to go for cs1020.
A trivial suggestion, but disclaimers would be good [indicating that problem sets can be very hard and time consuming].
Teaching feedback:
Prof. Gilbert is a very approachable lecturer, and his lectures
aren't too boring
, and I think he gets good points across.
Fun
and eloquent in explaining concepts.
First thing first, you are one of the best lecturers i've ever met in NUS. Excellent!
It's a tough mod, but taught
decently
.
I love the examples given during the lectures. It helps provide a clear pictorial view of what's going on, instead of lines after lines of code and/or mathematical formulations.