Subject Descriptions - Subject Information


Calendar: 2017 Undergraduate
Faculty: Faculty of Engineering and Information Sciences
Department: School of Computing and Information Technology


Subject Information
Subject Code CSCI203
Subject Name Algorithms and Data Structures
Credit Points 6
Pre-Requisites (CSIT110 or CSIT111) AND CSIT113
Co-Requisites None.
Restrictions None.
Equivalence None.
Assessment assignments 30%; lab exercises 10%, tutorial exercises 10%, exam 50%
General Subject Yes.
EFTSL (Non Weighted) 0.125
Non Weighted Student Contribution Amounts
Commonwealth Supported (HECS) Students Only
Pre-1997 Pre-2005 Post-2005 Post-2008 Post-2009 Post-2010
$ 1131  $ 1131  $ 1131  $ 1131  $ 1131  $ 1131 
Weighted Student Contribution Amounts
Commonwealth Supported (HECS) Students Only
Course
1771-Bachelor of Laws (Honours) (Direct Entry)
1777-Bachelor of Laws (Direct Entry)
1827-Bachelor of International Studies - Bachelor of Laws
1845-Bachelor of Information Technology - Bachelor of Laws
1852-Bachelor of Business Information Systems - Bachelor of Laws
351-Bachelor of Laws (Honours)
760-Bachelor of Communication and Media Studies - Bachelor of Laws
770-Bachelor of Laws (Graduate Entry)
771-Bachelor of Arts - Bachelor of Laws
771H-Bachelor of Arts - Bachelor of Laws
772-Bachelor of Creative Arts - Bachelor of Laws
773-Bachelor of Commerce - Bachelor of Laws
774-Bachelor of Mathematics - Bachelor of Laws
775-Bachelor of Science - Bachelor of Laws
775H-Bachelor of Science - Bachelor of Laws
775M-Course information not Found
779-Bachelor of Engineering - Bachelor of Laws
858-Bachelor of Journalism - Bachelor of Laws
Work Experience No
Tutorial Enrolment Information Students should use the SMP OnLine Tutorial System (via SOLS) to enrol in Tutorial/laboratory groups for this subject. Once enrolments are open a link to the subject will appear in Tutorial Enrolments.

Subject Availability
Session DXB UG Spring  (05-02-2017 to 03-06-2017)
Campus Dubai
Delivery Method On Campus
Instance Name Class 1
Quota 75
Course Restrictions No restrictions
Contact Hours  
Lecturer(s) and
Cons. times
Halim Khelalfa
Rahul Bijlani
Coordinator(s) and
Cons. times
Jun Shen
Instance Comment  
Census Date 28-02-2017

Subject Availability
Session INTI Subang Jaya Session 1  (06-03-2017 to 12-07-2017)
Campus INTI Subang Jaya
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours  
Lecturer(s) and
Cons. times
Pawani Rasaratnam
Coordinator(s) and
Cons. times
Ian Piper
Mark Freeman
Vincent Loh
Instance Comment  
Census Date 31-03-2017

Subject Availability
Session SIM Session 2  (01-04-2017 to 08-06-2017)
Campus Singapore Institute of Management
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours  
Lecturer(s) and
Cons. times
Ian Piper
Coordinator(s) and
Cons. times
Casey Chow
Instance Comment  
Census Date 14-04-2017

Subject Availability
Session SIM Session 3  (01-07-2017 to 07-09-2017)
Campus Singapore Institute of Management
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours  
Lecturer(s) and
Cons. times
Ian Piper
Coordinator(s) and
Cons. times
Casey Chow
Instance Comment  
Census Date 14-07-2017

Subject Availability
Session Spring  (24-07-2017 to 16-11-2017)
Campus Wollongong
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours 3 hours of lecture per week; one 2 hour lab
Lecturer(s) and
Cons. times
Ian Piper
Coordinator(s) and
Cons. times
Ian Piper
Instance Comment  
Census Date 31-08-2017

Subject Availability
Session INTI Subang Jaya Session 2  (31-07-2017 to 03-12-2017)
Campus INTI Subang Jaya
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours  
Lecturer(s) and
Cons. times
Pawani Rasaratnam
Coordinator(s) and
Cons. times
Ian Piper
Mark Freeman
Vincent Loh
Instance Comment  
Census Date 25-08-2017

Subject Description
Approaches to analysing algorithm complexity and implementation efficiency will be introduced; and used to motivate the development of appropriate abstract data types. Students will be taught to recognise the role of abstract data types and algorithms in solving real-world problems; and given the opportunity to implement solutions to such problems.


Subject Learning Outcomes
On successful completion of this subject, students will be able to:
1. Determine and compare the complexity of algorithms.
2. Choose and use appropriate data structures and algorithms for a wide class of problems.
3. Make effective use of abstract data types as a design technique and implement them using appropriate programming constructs.
4. Demonstrate an ability to code efficient implementations of algorithms using appropriate choices of abstract data types.


Textbook Information

Text book information is available via the UniShop website:



Search Criteria [Click here for help]
Subject Code / Name
Level
Department
Session
Campus
Delivery Method
General Subjects