Course Title: Computing Theory

Part A: Course Overview

Course Title: Computing Theory

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

COSC1105

City Campus

Postgraduate

140H Computer Science & Information Technology

Face-to-Face

Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

COSC1105

City Campus

Postgraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 2 2018,
Sem 2 2019

COSC1106

Bundoora Campus

Undergraduate

140H Computer Science & Information Technology

Face-to-Face

Sem 2 2006

COSC1107

City Campus

Undergraduate

140H Computer Science & Information Technology

Face-to-Face

Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

COSC1107

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 2 2018,
Sem 2 2019

COSC2087

RMIT University Vietnam

Undergraduate

140H Computer Science & Information Technology

Face-to-Face

Viet1 2015

COSC2235

Taylors College KL

Undergraduate

140H Computer Science & Information Technology

Face-to-Face

Offsh 1 11

Course Coordinator: Dr. Sebastian Sardina

Course Coordinator Phone: +61 3 9925 9824

Course Coordinator Email: sebastian.sardina@rmit.edu.au

Course Coordinator Location: 14.08.7D

Course Coordinator Availability: By appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

You must have successfully completed the following course before enrolling in this course:

Algorithms and Analysis

 


Course Description

Computing Theory introduces you to foundational issues in computer science. The emphasis is on understanding and applying foundational concepts and techniques. You will learn and apply fundamental theories of computing to computing problems. Topics include the study of formal models of computation and computability properties, measuring time requirements for a computation approaches to difficult problems, the use of grammars to specify syntax rules.


Objectives/Learning Outcomes/Capability Development

Program Learning Outcomes

This course contributes to the following Program Learning Outcomes in BP094 Bachelor of Computer Science and BP096 Bachelor of Software Engineering:

  1. Enabling Knowledge

You will gain skills as you apply knowledge effectively in diverse contexts.

  1. Critical Analysis

You will learn to accurately and objectively examine and consider computer science and information technology (IT) topics, evidence, or situations, in particular to:

  • Analyse and model requirements and constraints for the purpose of designing and implementing software artefacts and IT systems
  • Evaluate and compare designs of software artefacts and IT systems on the basis of organisational and user requirements.
  1. Problem Solving

Your capability to analyse problems and synthesise suitable solutions will be extended as you learn to:

  • Design and implement software solutions that accommodate specified requirements and constraints, based on analysis or modelling or requirements specification.


Course Learning Outcomes

Upon successful completion of this course you should be able to:

  • CLO 1: Identify the core concepts and notions of fundamental theories of computing.
  • CLO 2: Discriminate between core ideas of computation and computing technology.
  • CLO 3: Analyse and compare the characteristics of different types of computational models and problems and of different models of computation.
  • CLO 4: Design and implement solutions to a wide range of problems, including constructing grammars or automatons for given formal languages and specifying formal languages for given grammars or automatons.
  • CLO 5: Communicate clearly and effectively using the technical language of the field correctly.


Overview of Learning Activities

The learning activities included in this course are:

  • key concepts will be explained in lectures, classes or online, where syllabus material will be presented and the subject matter will be illustrated with demonstrations and examples;

 

A total of 120 hours of study is expected during this course, comprising:

Teacher-directed hours (48 hours): Lectures will take place twice a week, and introduce concepts and motivations for studying them. Students will work on set problems each week in tutorials, which will be based around working groups of 4 to 5 students. Regular online quizzes and major tests will provide regular feedback on progress. 

Student-directed hours (72 hours): You are expected to be self-directed, studying independently outside class to consolidate your understanding of the theory and practice.


Overview of Learning Resources

The course is supported by online tools, such as the Canvas learning management system and/or Google-based systems, which provide specific learning resources. See the RMIT Library Guide at http://rmit.libguides.com/compsci


Overview of Assessment

 

The assessment for this course comprises:

Note: This course has no hurdle requirements.

 

Assessment tasks

 

Assessment Component 1:  Assignments

Weighting 30%

This assessment task supports CLOs  1-5

 

Assessment Component 2: Class Tests/Quizzes

Weighting 20%

This assessment task supports CLOs  1-5

 

Assessment Component 3: End-of-semester Examination

Weighting 50% 

This assessment task supports CLOs  1-5

 

Please note that the breadth and depth of assessment tasks for postgraduate students will be greater than the tasks for undergraduate students.