Complex Systems
Unit of study table
Master of Complex Systems |
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|---|---|---|
| Students complete 72 credit points, comprising: | ||
| (a) 54 credit points of core units including: | ||
| (i) 24 credit points of foundational core units of study | ||
| (ii) 24 credit points of core complex systems units of study | ||
| (iii) 6 credit points of capstone units of study | ||
| (b) 6 credit points of advanced computing units of study | ||
| (c) 12 credit points of elective units of study | ||
Graduate Diploma in Complex Systems |
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| Students complete 48 credit points, comprising: | ||
| (a) 36 credit points of core units, including: | ||
| (i) 24 credit points of foundational core units of study | ||
| (ii) a minimum of 12 credit points of core complex systems units of study | ||
| (b) a maximum of 12 credit points of elective units of study. | ||
Specialisations |
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| (a) Completion of a specialisation is not a requirement of the course. | ||
| (b) Students have the option of completing one specialisation. | ||
| (c) A specialisation requires the completion of 12 credit points chosen from units of study listed for that specialisation. | ||
| The specialisations available are: | ||
| Engineering | ||
| Biosecurity | ||
| Transport | ||
| Research Methods |
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition |
|---|---|---|
Core units of study |
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Foundational core units |
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| COMP9001 Introduction to Programming |
6 | N INFO1110 or INFO1910 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or ENGG1810 |
| COMP9208 Artificial Intelligence and Society |
6 | A Competency in 1st year mathematics. Exposure to computer programming would be useful but not mandatory |
| PMGT5886 System Dynamics Modelling for PM |
6 | |
| STAT5002 Introduction to Statistics |
6 | A HSC Mathematics |
Complex Systems core units |
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| CSYS5010 Introduction to Complex Systems |
6 | |
| CSYS5020 Interdependent Civil Systems |
6 | |
| CSYS5030 Information Theory and Self-Organisation |
6 | A Competency in 1st year mathematics, and basic computer programming skills are assumed. Competency in 1st year undergraduate level statistics (for example, covering probabilities, conditional probabilities, Gaussian distribution, correlations, statistical significance/hypothesis testing and p-values). An exposure to linear algebra would be useful but not mandatory |
| CSYS5040 Criticality in Dynamical Systems |
6 | A Mathematics at first-year undergraduate level. Some familiarity with mathematical and computational principles at an undergraduate university level (for example, differential calculus or linear algebra). Familiarity with a programming language at a beginners level for data analysis |
Advanced Computing units |
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| COMP5048 Visual Analytics |
6 | A Experience with data structures and algorithms as covered in COMP9103 or COMP9003 or COMP2123 or COMP2823 or INFO1105 or INFO1905 (or equivalent UoS from different institutions) N COMP4448 or OCMP5048 |
| COMP5313 Large Scale Networks |
6 | A Algorithmic skills gained through units such as COMP2123 or COMP2823 or COMP3027 or COMP3927 or COMP9007 or COMP9123 or equivalent. Basic probability knowledge N COMP4313 |
Complex Systems capstone |
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| Students must complete 48 credit points from Core and Elective units of study before taking Complex Systems Capstone Project unit. | ||
| CSYS5050 Complex Systems Capstone Project A |
6 | P 48 credit points including CSYS5010 |
Electives |
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| CHNG9202 Chemical Engineering Modelling and Analysis |
6 | A Enrolment in this unit of study assumes that first year undergraduate core maths, science and engineering UoS (or their equivalent) have been successfully completed N CHNG2802 or CHNG5702 |
| CISS6004 Health and Security |
6 | |
| COMP5318 Machine Learning and Data Mining |
6 | A Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions). Discrete mathematics and probability (e.g. MATH1064 or equivalent); linear algebra and calculus (e.g. MATH1061 or equivalent) N COMP4318 or OCMP5318 |
| CSYS5060 Complex Systems Research Project A |
6 | P CSYS5010 |
| CSYS5061 Complex Systems Research Project B |
6 | P CSYS5010 C CSYS5060 Research Project A is meant to be done before or in parallel with Research Project B |
| DATA5207 Data Analysis in the Social Sciences |
6 | N DATA4207 |
| ELEC5208 Intelligent Electricity Networks |
6 | A Fundamentals of Electricity Networks, Control Systems and Telecommunications |
| ELEC5509 Mobile Networks |
6 | A ELEC3505 or ELEC9505 and ELEC3506 or ELEC9506. Basically, students need to know the concepts of data communications and mobile communications. If you are not sure, please contact the instructor |
| ELEC9103 Simulations and Numerical Solutions in Eng |
6 | A ELEC9703. Understanding of the fundamental concepts and building blocks of electrical and electronics circuits and aspects of professional project management, teamwork, and ethics N ELEC5723 or ELEC2103 or COSC1001 or COSC1901 |
| ENVI5809 Environmental Simulation Modelling |
6 | A This unit assumes a sound understanding of scientific principles, HSC level Mathematics and understanding of basic statistics |
| ENVI5904 Methods in Applied Ecology |
6 | |
| GEOG5001 Geographic Information Science A |
6 | A This unit assumes a sound understanding of scientific principles, HSC level mathematics and understanding of basic statistics |
| GEOG5004 Environmental Mapping and Monitoring |
6 | A This unit assumes a sound understanding of scientific principles, HSC level mathematics and understanding of basic statistics |
| HTIN5003 Health Technology Evaluation |
6 | N HTIN4003 |
| HTIN5004 Integrated Approaches to Chronic Disease |
6 | |
| INFO5060 Data Analytics and Business Intelligence |
6 | A Basic knowledge of information systems as covered in COMP5206 or ISYS2160 (or equivalent UoS from different institutions) |
| ITLS5020 Production and Operations Management |
6 | N TPTM6155 or TPTM5001 or ITLS5000 or ITLS6008 |
| ITLS5050 Introductory Supply Chain Analysis |
6 | C ITLS5020 or ITLS5000 or TPTM5001 N TPTM6495 or ITLS5200 or ITLS6203 or MMGT6012 |
| ITLS5100 Transport and Infrastructure Foundations |
6 | N TPTM6241 |
| ITLS6002 Supply Chain Planning and Design |
6 | P (ITLS5020 or ITLS5000 or TPTM5001) and (ITLS5050 or ITLS5200 or TPTM6495) and (ITLS6201 or ITLS6101) and (ITLS6202 or ITLS6003) C ITLS6010 or ITLS6008 N TPTM6190 |
| ITLS6007 Humanitarian Logistics |
6 | N TPTM6390 |
| ITLS6102 Transport Modelling and Forecasting |
6 | N TPTM6350 |
| ITLS6111 Spatial Analytics |
6 | A Basic knowledge of Excel is assumed. N ITLS6107 or TPTM6180 This unit will use R programming language to perform statistical analyses and spatial analyses. No prior programming knowledge is required. |
| PHYS5031 Ecological Econ and Sustainable Analysis |
6 | |
| PHYS5032 Techniques for Sustainability Analysis |
6 | Minimum class size of 5 students. |
| PMGT5875 Project Innovation Management |
6 | |
| PMGT5897 Disaster Project Management |
6 | |
| PUBH5010 Epidemiology Methods and Uses |
6 | N BSTA5011 |
| QBUS5001 Foundation in Data Analytics for Business |
6 | A Students should be capable of reading data in tabulated form and working with Microsoft EXCEL and doing High School level of mathematics N ECMT5001 or QBUS5002 |
| QBUS6810 Machine Learning for Business |
6 | P (ECMT5001 or QBUS5001) and (a mark of 65 or greater in BUSS6002 or COMP5310) N STAT5003 or COMP5318 |
| QBUS6840 Predictive Analytics |
6 | P (QBUS5001 or ECMT5001 or STAT5003) and (a mark of 65 or greater in BUSS6002 or COMP5310 or COMP5318) |
| SUST5004 Sustainable Development and Population Health |
6 | This unit of study involves essay-writing. Academic writing skills equivalent to HSC Advanced English or significant consultation via the Writing Hub is assumed. |
Specialisations |
||
| Completion of a specialisation is not a requirement of the course. To be eligible for a specialisation, a candidate must complete 12 credit points chosen from that specialisation. | ||
Biosecurity |
||
| CISS6004 Health and Security |
6 | |
| DATA5207 Data Analysis in the Social Sciences |
6 | N DATA4207 |
| ENVI5809 Environmental Simulation Modelling |
6 | A This unit assumes a sound understanding of scientific principles, HSC level Mathematics and understanding of basic statistics |
| ENVI5904 Methods in Applied Ecology |
6 | |
| GEOG5001 Geographic Information Science A |
6 | A This unit assumes a sound understanding of scientific principles, HSC level mathematics and understanding of basic statistics |
| GEOG5004 Environmental Mapping and Monitoring |
6 | A This unit assumes a sound understanding of scientific principles, HSC level mathematics and understanding of basic statistics |
| HTIN5003 Health Technology Evaluation |
6 | N HTIN4003 |
| HTIN5004 Integrated Approaches to Chronic Disease |
6 | |
| PHYS5031 Ecological Econ and Sustainable Analysis |
6 | |
| PHYS5032 Techniques for Sustainability Analysis |
6 | Minimum class size of 5 students. |
| PUBH5010 Epidemiology Methods and Uses |
6 | N BSTA5011 |
| SUST5004 Sustainable Development and Population Health |
6 | This unit of study involves essay-writing. Academic writing skills equivalent to HSC Advanced English or significant consultation via the Writing Hub is assumed. |
Engineering |
||
| CHNG9202 Chemical Engineering Modelling and Analysis |
6 | A Enrolment in this unit of study assumes that first year undergraduate core maths, science and engineering UoS (or their equivalent) have been successfully completed N CHNG2802 or CHNG5702 |
| COMP5318 Machine Learning and Data Mining |
6 | A Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions). Discrete mathematics and probability (e.g. MATH1064 or equivalent); linear algebra and calculus (e.g. MATH1061 or equivalent) N COMP4318 or OCMP5318 |
| DATA5207 Data Analysis in the Social Sciences |
6 | N DATA4207 |
| ELEC5208 Intelligent Electricity Networks |
6 | A Fundamentals of Electricity Networks, Control Systems and Telecommunications |
| ELEC5509 Mobile Networks |
6 | A ELEC3505 or ELEC9505 and ELEC3506 or ELEC9506. Basically, students need to know the concepts of data communications and mobile communications. If you are not sure, please contact the instructor |
| ELEC9103 Simulations and Numerical Solutions in Eng |
6 | A ELEC9703. Understanding of the fundamental concepts and building blocks of electrical and electronics circuits and aspects of professional project management, teamwork, and ethics N ELEC5723 or ELEC2103 or COSC1001 or COSC1901 |
| INFO5060 Data Analytics and Business Intelligence |
6 | A Basic knowledge of information systems as covered in COMP5206 or ISYS2160 (or equivalent UoS from different institutions) |
| QBUS5001 Foundation in Data Analytics for Business |
6 | A Students should be capable of reading data in tabulated form and working with Microsoft EXCEL and doing High School level of mathematics N ECMT5001 or QBUS5002 |
| QBUS6810 Machine Learning for Business |
6 | P (ECMT5001 or QBUS5001) and (a mark of 65 or greater in BUSS6002 or COMP5310) N STAT5003 or COMP5318 |
| QBUS6840 Predictive Analytics |
6 | P (QBUS5001 or ECMT5001 or STAT5003) and (a mark of 65 or greater in BUSS6002 or COMP5310 or COMP5318) |
Transport |
||
| COMP5318 Machine Learning and Data Mining |
6 | A Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions). Discrete mathematics and probability (e.g. MATH1064 or equivalent); linear algebra and calculus (e.g. MATH1061 or equivalent) N COMP4318 or OCMP5318 |
| DATA5207 Data Analysis in the Social Sciences |
6 | N DATA4207 |
| ELEC5509 Mobile Networks |
6 | A ELEC3505 or ELEC9505 and ELEC3506 or ELEC9506. Basically, students need to know the concepts of data communications and mobile communications. If you are not sure, please contact the instructor |
| ELEC5208 Intelligent Electricity Networks |
6 | A Fundamentals of Electricity Networks, Control Systems and Telecommunications |
| INFO5060 Data Analytics and Business Intelligence |
6 | A Basic knowledge of information systems as covered in COMP5206 or ISYS2160 (or equivalent UoS from different institutions) |
| ITLS5020 Production and Operations Management |
6 | N TPTM6155 or TPTM5001 or ITLS5000 or ITLS6008 |
| ITLS5050 Introductory Supply Chain Analysis |
6 | C ITLS5020 or ITLS5000 or TPTM5001 N TPTM6495 or ITLS5200 or ITLS6203 or MMGT6012 |
| ITLS5100 Transport and Infrastructure Foundations |
6 | N TPTM6241 |
| ITLS6002 Supply Chain Planning and Design |
6 | P (ITLS5020 or ITLS5000 or TPTM5001) and (ITLS5050 or ITLS5200 or TPTM6495) and (ITLS6201 or ITLS6101) and (ITLS6202 or ITLS6003) C ITLS6010 or ITLS6008 N TPTM6190 |
| ITLS6007 Humanitarian Logistics |
6 | N TPTM6390 |
| ITLS6102 Transport Modelling and Forecasting |
6 | N TPTM6350 |
| ITLS6111 Spatial Analytics |
6 | A Basic knowledge of Excel is assumed. N ITLS6107 or TPTM6180 This unit will use R programming language to perform statistical analyses and spatial analyses. No prior programming knowledge is required. |
| QBUS5001 Foundation in Data Analytics for Business |
6 | A Students should be capable of reading data in tabulated form and working with Microsoft EXCEL and doing High School level of mathematics N ECMT5001 or QBUS5002 |
| QBUS6810 Machine Learning for Business |
6 | P (ECMT5001 or QBUS5001) and (a mark of 65 or greater in BUSS6002 or COMP5310) N STAT5003 or COMP5318 |
| QBUS6840 Predictive Analytics |
6 | P (QBUS5001 or ECMT5001 or STAT5003) and (a mark of 65 or greater in BUSS6002 or COMP5310 or COMP5318) |
Research Methods |
||
| CSYS5060 Complex Systems Research Project A |
6 | P CSYS5010 |
| CSYS5061 Complex Systems Research Project B |
6 | P CSYS5010 C CSYS5060 Research Project A is meant to be done before or in parallel with Research Project B |
