Software Engineering
Unit of study table
Master of Engineering (Software) |
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| To qualify for the award of the Master of Engineering in this stream, a candidate must complete 72 credit points, including: |
| 1. 42 credit points of Stream units, consisting of: |
| (a) 30 credit points of Stream units, including: |
| (i) 24 credit points of Stream Core units, and |
| (ii) 6 credit points of Stream Selective units |
| (b) 12 credit points of elective units comprising: |
| (i) A maximum of 12 credit points of Stream Electives |
| (ii) A maximum of 12 credit points of additional Engineering Management and Leadership units of study |
| (iii) A maximum of 6 credit points of Breadth elective units of study |
| 2. A minimum of 12 credit points of Research units |
| 3. 12 credit points of Engineering Management and Leadership units |
| 4. A maximum of 6 credit points of Breadth Elective units |
| Candidates who have been granted 24 credit points of Reduced Volume Learning (RVL), must complete 48 credit points including: |
| 1. 30 credit points of Stream units, consisting of: |
| (a) 30 credit points of Stream units, including: |
| (i) 24 credit points of Stream Core units, and |
| (ii) 6 credit points of Stream Selective units |
| 2. A minimum of 12 credit points of Research units |
| 3. 6 credit points of Engineering Management & Leadership units |
| – Breadth Elective units are not available for candidates with RVL |
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition |
|---|---|---|
Stream Core units |
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| ELEC5618 Software Quality Engineering |
6 | A Writing programs with multiple functions or methods in multiple files; design of complex data structures and combination in non trivial algorithms; use of an integrated development environment; software version control systems |
| ELEC5619 Object Oriented Application Frameworks |
6 | A Java programming, and some web development experience are essential. Databases strongly recommended |
| ELEC5620 Model Based Software Engineering |
6 | A A programming language, basic maths |
| ELEC5622 Signals, Software and Health |
6 | A Mathematics (linear algebra and probabilities) and basic programming skills (python/matlab/C++/java) |
Stream Selective units |
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| COMP5047 Pervasive Computing |
6 | A ELEC1601 and (COMP2129 or COMP2017 or COMP9017). Background in programming and operating systems that is sufficient for the student to independently learn new programming tools from standard online technical materials N COMP4447 |
| COMP5416 Advanced Network Technologies |
6 | A COMP3221 or ELEC3506 or ELEC9506 or ELEC5740 or COMP5116 or COMP9121 N COMP4416 |
| COMP5424 Information Technology in Biomedicine |
6 | A Experience with software development as covered in SOFT2412 or COMP9103 or COMP9003 (or equivalent UoS from different institutions) N COMP4424 |
| ELEC5614 Real Time Computing |
6 | A COMP2129 Operating Systems and Machine Principles and ELEC3607 Embedded Systems N MECH5701 |
| ELEC5616 Computer and Network Security |
6 | A A programming language, basic maths |
Stream Elective units |
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| ELEC5304 Intelligent Visual Signal Understanding |
6 | A Mathematics (e.g. probability and linear algebra) and programming skills (e.g. Matlab/Java/Python/C++) |
| ELEC5305 Acoustics, Speech and Signal Processing |
6 | A (ELEC2302 or ELEC9302) and (ELEC3305 or ELEC9305). Linear algebra, fundamental concepts of signals and systems as covered in ELEC2302/ELEC9302, fundamental concepts of digital signal processing as covered in ELEC3305/9305. It would be unwise to attempt this unit without the assumed knowledge- if you are not sure, please contact the instructor |
| ELEC5306 Video Intelligence and Compression |
6 | A Basic understanding of digital signal processing (filtering, DFT) and programming skills (e.g. Matlab/Java/Python/C++) |
| ELEC5307 Advanced Signal Processing with Deep Learning |
6 | A Mathematics (e.g., probability and linear algebra) and programming skills (e.g. Matlab/Java/Python/C++) |
| ELEC5308 Intelligent Information Engineering Practice |
6 | A Students must have a good understanding of Linear algebra and basic mathematics, Basic Programming skills in C, Python or Matlab |
| ELEC5623 Applied Generative AI in Engineering |
6 | A Students must have a basic understanding of artificial intelligence, software engineering and be proficient in Linear algebra, Python Programming |
Research units |
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| ELEC5020 Capstone Project A |
6 | P 96 credit points from MPE degree program or 48 credit points from the MPE(Accel) program or 24 credit points from the ME program (including any credit for previous study) |
| ELEC5021 Capstone Project B |
6 | P ELEC5020 N ELEC5022 or ELEC5222 or ELEC5223 |
| ELEC5022 Capstone Project B Extended |
12 | P 24 credit points in the Master of Engineering and WAM >=70 or 96 credit points in the Master of Professional Engineering and WAM >=70 or 48 credit points from MPE(Accel) program and WAM >=70 N ELEC5021 or ELEC5222 or ELEC5223 |
| ELEC5222 Dissertation A |
12 | N ELEC8901 or ENGG5223 or ENGG5222 or ELEC8902 In order to enrol in a project, students must first secure an academic supervisor in an area that they are interested. The topic of your project must be determined in discussion with the supervisor. The supervisor can come from any of the Engineering Departments, however, they need to send confirmation of their supervision approval to the Postgraduate Administrator. |
| ELEC5223 Dissertation B |
12 | P ELEC5222 N ELEC8901 or ELEC8902 or ENGG5222 or ENGG5223 In order to enrol in a project, students must first secure an academic supervisor in an area that they are interested. The topic of your project must be determined in discussion with the supervisor. The supervisor can come from any of the Engineering Departments, however, they need to send confirmation of their supervision approval to the Postgraduate Administrator. |
| With permission from the Program Director candidates progressing with distinction (75%) average or higher results may replace ELEC5020 , ELEC5021 and 12 credit points of electives with ELEC5222 & ELEC5223 Dissertation A & B. | ||
| A candidate who has been granted RVL and who is eligible to undertake the extended capstone project or dissertation may be granted exemption of up to 12 credit points of specialist units. | ||
Major Industrial Project |
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| Candidates undertaking the Major Industrial Project take ELEC5010 in place of ELEC5020/ELEC5021 Capstone Project A and B and 12 credit points of Elective units of study. | ||
| ELEC5010 Major Industrial Project |
24 | A WAM >= 70 in prior semester enrolment N ELEC5020 or ELEC5021 or ELEC5022 or ELEC5222 or ELEC5223 or ENGG5217 |
