Part A: Course Overview

Course Title: Algorithms and Analysis

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

COSC3119

City Campus

Postgraduate

175H Computing Technologies

Face-to-Face

 Sem 1 2025

COSC3120

RMIT University Vietnam

Postgraduate

175H Computing Technologies

Face-to-Face

 Viet1 2025

Course Coordinator: Dr Elham Naghizade

Course Coordinator Phone: -

Course Coordinator Email: e.naghizade@rmit.edu.au

Course Coordinator Availability: By appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Recommended Prior Study 
You should have satisfactorily completed or received credit for the following course/s before you commence this course:

If you have completed prior studies at RMIT or another institution that developed the skills and knowledge covered in the above course/s you may be eligible to apply for credit transfer.

Alternatively, if you have prior relevant work experience that developed the skills and knowledge covered in the above course/s you may be eligible for recognition of prior learning.

Please follow the link for further information on how to apply for credit for prior study or experience.


Course Description

The main objective of this course is for you to acquire the tools and techniques necessary to propose practical algorithmic solutions to real-world problems which still allow strong theoretical bounds on time and space usage. You will study a broad variety of important and useful algorithms and data structures in different areas of applications, and will concentrate on fundamental algorithms. You will spend a significant time on each algorithm to understand its essential characteristics and to respect its subtleties.


Objectives/Learning Outcomes/Capability Development

Program Learning Outcomes

This course contributes to the program learning outcomes for the following program(s):

MC271 - Master of Artificial Intelligence

PLO 1    Enabling Knowledge
PLO 2    Critical Analysis
PLO 3    Problem Solving

MC208 - Master of Information Technology

PLO 1    Enabling Knowledge
PLO 2    Critical Analysis
PLO 3    Problem Solving
PLO 4    Communication
PLO 6    Teamwork

For more information on the program learning outcomes for your program, please see the program guide.


Upon successful completion of this course, you will be able to:

  1. Compare, contrast, and apply the key algorithmic design paradigms: brute force, divide and conquer, decrease and conquer, transform and conquer, greedy, dynamic programming and iterative improvement;
  2. Compare, contrast, and apply key data structures: trees, lists, stacks, queues, hash tables and graph representations;
  3. Define, compare, analyse, and solve general algorithmic problem types: sorting, searching, graphs and geometric;
  4. Theoretically compare and analyse the time complexities of algorithms and data structures; and 
  5. Implement, empirically compare, and apply fundamental algorithms and data structures to real-world problems.    


Overview of Learning Activities

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Note: This course has no hurdle requirements.

Assessment Tasks

Assessment Task 1: Weekly Quizzes

Weighting 10%  
 
This assessment task supports CLOs 1, 2, 3 & 4 

Assessment Task 2: Mid-semester Challenge

Weighting 20%
 
This assessment task supports CLOs 1, 2, 3, 4 & 5 

Assessment Task 3: Assignment 2

Weighting 30%
 
This assessment supports CLOs 1, 2, 3, 4 & 5 

Assessment Task 4: End-of-semester Timed and Timetabled Exercises

Weighting 40% 
This assessment supports CLOs 1, 2, 3, 4 & 5
 

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.