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COMP5211: Algorithms (2010 - Semester 1)

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Unit: COMP5211: Algorithms (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Computer Science
Unit Coordinator/s: Professor Eades, Peter
Session options: Semester 1, Semester 2
Versions for this Unit:
Site(s) for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: The study of algorithms is a fundamental aspect of computing. This unit of study covers algorithms and data structures. It gives an overview of computational thinking based on a variety of algorithmic concepts. Students will gain essential knowledge in computer science, including basic concepts in data structures, algorithms, and intractability, using paradigms such as dynamic programming, divide and conquer, greed, local search, network flow, and randomisation, as well NP-hardness. Examples in graph algorithms, scheduling algorithms, and geometric algorithms will be covered.
Assumed Knowledge: This unit of study assumes that students have general knowledge of mathematics (especially Discrete Math) and problem solving. Having moderate knowledge about Data structure can also help students to better understand the concepts of Algorithms will be taught in this course.
Lecturer/s: Professor Eades, Peter
Timetable: COMP5211 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Independent Study 5.00 13
2 Lecture 2.00 1 13
3 Tutorial 1.00 1 13
T&L Activities: Lecture: Lecture

Tutorial: Tutorial

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
Understand main concepts of Graphs. Design and Problem Solving Skills (Level 4)

For explanation of attributes and levels see Engineering/IT Graduate Attribute Matrix 2009.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Design and Problem Solving Skills (Level 4)
1. Knowledge of fundamental algorithms for several problems, including graphs, greedy agorithms, divide-and-conquer, dynamic programming, and network flow as well as basic concepts of NP-completeness.
2. Collaboration in lectures/tutorials and exchange of ideas to solve algorithmic problems.
3. Ability to understand and analyze given algorithms as well as ability to design algorithmic solutions for given problems.
4. Students will practice their writing presentation skills.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Assignment No 20.00 Week 8
2 Assignment No 20.00 Week 12
3 Final Exam No 60.00 Exam Period
Assessment Description: Assignment: Assignment 1

Assignment: Assignment 2

Final Exam: Final Exam
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: The faculty attempts to maintain consistency and quality in its T&L operations by adhering to Academic Board policy. These policies can be found on the Central Policy Online site. A brief summary of the relevant T&L policies that should be referred to while filling in these forms can be found at the Faculty of Engineering and Information Technologies Policy Page.
Online Course Content:

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar

Week Description
Week 1 Introduction
Week 2 Basic Algorithm Analysis
Week 3 Graphs
Week 4 Greedy Algorithms
Week 5 Divide and Conquer
Week 6 Dynamic Programming
Week 7 Network flow
Week 8 Anzac day holiday
Assessment Due: Assignment
Week 9 NP-completeness and intractability
Week 10 Approximation
Week 11 Local search
Week 12 Randomized Algorigthms
Assessment Due: Assignment
Week 13 Review week
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Master of Professional Engineering (Software) 2013, 2014
Software Engineering / Arts 2011, 2012, 2013, 2014
Software Engineering / Commerce 2010, 2011, 2012, 2013, 2014
Software Engineering / Medical Science 2011, 2012, 2013, 2014
Software Engineering / Project Management 2012, 2013, 2014
Software Engineering / Science 2011, 2012, 2013, 2014
Master of Engineering (including Grad Cert & Grad Dip) 2014

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Design and Problem Solving Skills (Level 4) Yes 0%

These goals are selected from Engineering/IT Graduate Attribute Matrix 2009 which defines overall goals for courses where this unit is primarily offered. See Engineering/IT Graduate Attribute Matrix 2009 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.