Faculty of Engineering

Master of Computer Science (advanced entry) (Work Integrated Pathway) (2024)


Note: This course version applies only to students first enrolling in 2024.
WARNING: This course version is currently under review and is subject to change.


1. Overview

Course: Master of Computer Science (advanced entry) (Work Integrated Pathway) (2024)
CP Required: 96
Min FT Duration: 2.00 Years
Min PT Duration: N/A
Faculty/School: Faculty of Engineering
Years Offered: 2025, 2024

2. Requirements

Summary

Students must complete 96 credit points as follows:

► A minimum 24 credit points and maximum 30 credit points of Foundation units, including:

    - 12 credit points of Foundation Core units,

    - 6 credit points of Foundation Programming Selective units, and

    - 6 credit points of Foundation Networking Selective units

► 18 credit points of Core units

► A minimum 24 credit points of Specialist units

► A maximum 12 credit points of Elective units

► 12 credit points of Capstone Pathway units, OR

► 24 credit points of Research Pathway units, OR

► 24 credit points of Work Integrated Pathway units

The completion of a specialisation is not mandatory. If a student chooses to do a specialisation, it must be completed within the Specialist units credit points described above. Units of study counted towards one specialisation may not count toward any other specialisation completed

University Handbook

Refer to the university handbook at http://sydney.edu.au/handbooks/ for more information.

3. Semesters

Year 0 - Planning your degree

Type CP CP From

Note: Work Integrated Pathway | Important information

Students can view all available specialisations under the `Major/Pathways` tab. We strongly recommend that students complete their Foundation units before enrolling in specialisation units.

The Specialist units chosen may contribute towards a designated Specialisation. See the Majors/Pathways tab for details of each Specialisation.

Students who have completed a minimum of 48 credit points with at least Distinction average marks may take the Work Integrated Pathway. The Work Integrated Pathway must be taken during the last semester of studies.

In addition to this page, students should refer to the resources available on the School of Computer Science Canvas page https://canvas.sydney.edu.au/courses/15961/pages/master-of-computer-science-mcs-2

This includes details on academic advising and a link to FAQs specifically for Master of Computer Science students, including those pursuing a Graduate Certificate or Graduate Diploma.

Year 1 - Semester 1

Type CP CP From
6 Select from INFO5990: Professional Practice in IT
6 Select from INFO6007: Project Management in IT
6 Select from INFO5992: Understanding IT Innovations
6 Select from Unit Block:
Computer Science Specialist units

Year 1 - Semester 2

Type CP CP From
6 Select from Unit Block:
Computer Science Specialist units
6 Select from Unit Block:
Computer Science Specialist units
6 Select from Unit Block:
Computer Science Specialist units
6 Select from Unit Block:
Computer Science Specialist units

Year 2 - Semester 1

Type CP CP From
6 Select from Unit Block:
Computer Science Specialist units
6 Select from Unit Block:
Computer Science Specialist units
6 Select from Unit Block:
Computer Science Specialist units
List
6 Select from Unit Blocks:
Computer Science Foundation units
Computer Science Specialist units
Computer Science Elective units

Year 2 - Semester 2

Type CP CP From
24 Select from COMP5802: Work Integrated Project

4. Pathways

1. Algorithms and Theory Specialisation

Type CP CP From
24 Select from COMP5045: Computational Geometry
COMP5270: Randomised and Advanced Algorithms
COMP5530: Discrete Optimisation
CSYS5030: Information Theory and Self-Organisation

2. Cybersecurity Specialisation

Type CP CP From
24 Select from COMP5618: Applied Cybersecurity
CSEC5614: Data Privacy: Theory and Practice
CSEC5616: Cybersecurity Engineering
INFO5301: Information Security Management

3. Data Science and AI Specialisation

Type CP CP From
24 Select from COMP5310: Principles of Data Science
COMP5318: Machine Learning and Data Mining
COMP5339: Data Engineering
STAT5003: Computational Statistical Methods

4. Digital Media Specialisation

Type CP CP From
24 Select from COMP5405: Digital Media Computing
COMP5415: Multimedia Design and Authoring
COMP5425: Multimedia Retrieval
COMP5427: Usability Engineering

5. Human-Computer Interaction Specialisation

Type CP CP From
24 Select from COMP5047: Pervasive Computing
COMP5048: Visual Analytics
COMP5427: Usability Engineering
IDEA9106: Design Thinking

6. Networks and Distributed Systems Specialisation

Type CP CP From
24 Select from COMP5216: Mobile Computing
COMP5313: Large Scale Networks
COMP5416: Advanced Network Technologies
COMP5426: Parallel and Distributed Computing

7. Software Engineering Specialisation

Type CP CP From
24 Select from COMP5347: Web Application Development
COMP5348: Enterprise Scale Software Architecture
ELEC5618: Software Quality Engineering
ELEC5620: Model Based Software Engineering

8. Computer Science Specialist Units (unspecified specialisation)

Type CP CP From
24 Select from COMP5045: Computational Geometry
COMP5046: Natural Language Processing
COMP5047: Pervasive Computing
COMP5216: Mobile Computing
COMP5270: Randomised and Advanced Algorithms
COMP5313: Large Scale Networks
COMP5318: Machine Learning and Data Mining
COMP5339: Data Engineering
COMP5347: Web Application Development
COMP5348: Enterprise Scale Software Architecture
COMP5349: Cloud Computing
COMP5405: Digital Media Computing
COMP5415: Multimedia Design and Authoring
COMP5416: Advanced Network Technologies
COMP5425: Multimedia Retrieval
COMP5426: Parallel and Distributed Computing
COMP5427: Usability Engineering
COMP5530: Discrete Optimisation
COMP5618: Applied Cybersecurity
CSEC5614: Data Privacy: Theory and Practice
CSYS5030: Information Theory and Self-Organisation
ELEC5618: Software Quality Engineering
ELEC5620: Model Based Software Engineering
IDEA9106: Design Thinking
INFO5301: Information Security Management
STAT5003: Computational Statistical Methods

5. Unit Blocks

Block 1 - Computer Science Core units (Min CP: 18,Max CP: 18)

Unit Code Unit Name CP Sessions Offered
INFO5990 Professional Practice in IT 6 Semester 1
Semester 2
INFO5992 Understanding IT Innovations 6 Semester 1
Semester 2
INFO6007 Project Management in IT 6 Semester 1
Semester 2

Block 2 - Computer Science Foundation units (Max CP: 30)

Unit Code Unit Name CP Sessions Offered
COMP9001 Introduction to Programming 6 Semester 1
Semester 2
COMP9003 Object-Oriented Programming 6 Semester 1
Semester 2
COMP9017 Systems Programming 6 Semester 1
COMP9110 System Analysis and Modelling 6 Semester 1
COMP9120 Database Management Systems 6 Semester 1
Semester 2
COMP9121 Design of Networks & Distributed Systems 6 Semester 2
COMP9123 Data Structures and Algorithms 6 Semester 1
Semester 2
COMP9201 Software Construction and Design 1 6 Semester 2
COMP9601 Computer and Network Organisation 6 Semester 1
STAT5002 Introduction to Statistics 6 Semester 1
Semester 2

Block 3 - Computer Science Specialist units (Min CP: 24,Max CP: 48)

Unit Code Unit Name CP Sessions Offered
COMP5045 Computational Geometry 6 Semester 1
COMP5046 Natural Language Processing 6 Semester 1
COMP5047 Pervasive Computing 6 Semester 2
COMP5048 Visual Analytics 6 Semester 1
Semester 2
COMP5216 Mobile Computing 6 Semester 2
COMP5270 Randomised and Advanced Algorithms 6 Semester 1
COMP5310 Principles of Data Science 6 Semester 1
Semester 2
COMP5313 Large Scale Networks 6 Semester 1
COMP5318 Machine Learning and Data Mining 6 Semester 1
Semester 2
COMP5339 Data Engineering 6 Semester 1
Semester 2
COMP5347 Web Application Development 6 Semester 1
COMP5348 Enterprise Scale Software Architecture 6 Semester 2
COMP5349 Cloud Computing 6 Semester 1
COMP5405 Digital Media Computing 6 Semester 1
COMP5415 Multimedia Design and Authoring 6 Semester 2
COMP5416 Advanced Network Technologies 6 Semester 2
COMP5425 Multimedia Retrieval 6 Semester 1
COMP5426 Parallel and Distributed Computing 6 Semester 1
COMP5427 Usability Engineering 6 Semester 1
COMP5530 Discrete Optimisation 6 Semester 2
COMP5618 Applied Cybersecurity 6 Semester 2
CSEC5614 Data Privacy: Theory and Practice 6 Semester 2
CSEC5616 Cybersecurity Engineering 6 Semester 1
Semester 2
CSYS5030 Information Theory and Self-Organisation 6 Semester 2
ELEC5618 Software Quality Engineering 6 Semester 1
ELEC5620 Model Based Software Engineering 6 Semester 2
IDEA9106 Design Thinking 6 Semester 1
Semester 2
INFO5301 Information Security Management 6 Semester 1
Semester 2
STAT5003 Computational Statistical Methods 6 Semester 1
Semester 2

Block 4 - Computer Science Elective units (Max CP: 12)

Unit Code Unit Name CP Sessions Offered
CISS6022 Cybersecurity 6 Semester 2
DATA5207 Data Analysis in the Social Sciences 6 Semester 1
Int December
ELEC5507 Error Control Coding 6 Semester 1
ELEC5508 Wireless Engineering 6 Semester 2
ELEC5509 Mobile Networks 6 Semester 1
ELEC5510 Satellite Communication Systems 6 Semester 2
ELEC5514 IoT Wireless Sensing and Networking 6 Semester 2
ELEC5517 Software Defined Networks 6 Semester 2
ELEC5619 Object Oriented Application Frameworks 6 Semester 2
INFO5010 IT Advanced Topic A 6 Semester 1
Semester 2
INFO5011 IT Advanced Topic B 6 Semester 1
Semester 2

Block 5 - Computer Science Work Integrated units (Min CP: 24,Max CP: 24)

Unit Code Unit Name CP Sessions Offered
COMP5802 Work Integrated Project 24 Semester 1
Semester 2

Note: Work Integrated Learning Units

Candidates in the Work Integrated Pathway must take the 24 credit point unit of study, COMP5802 Work Integrated Project.

Students who have completed a minimum of 48 credit points with at least Distinction average marks may take the Work Integrated Pathway. The Work Integrated Pathway must be taken during the last semester of studies.