You will complete:

3 x Data Science core subjects
2 x Computing professional core subjects
3 x Data Science specialist elective subjects
1 x capstone project or research project
Elective or foundation units
You can choose to undertake one of the following specialisations as part of this degree:

Data Engineering
Machine Learning

Unit of study	Credit points	A: Assumed knowledge P: Prerequisites
C: Corequisites N: Prohibition
Core units of study
Data Science core units of study
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
COMP5310
Principles of Data Science	6	A Good understanding of relational data model and database technologies as covered in ISYS2120 or COMP9120 (or equivalent UoS from different institutions)
N INFO3406 OR OCMP5310
STAT5003
Computational Statistical Methods	6	A STAT5002 or equivalent introductory statistics course with a statistical computing component
Professional core units of study
INFO5990
Professional Practice in IT	6	
A Students enrolled in INFO5990 are assumed to have previously completed a Bachelor's degree in some area of IT, or have completed a Graduate Diploma in some area of IT, or have many years experience as a practising IT professional
N OINF5990

The main focus of the subject is to provide students with the necessary tools, basic skills, experience and adequate knowledge so they develop an awareness and an understanding of the responsibilities and issues associated with professional conduct and practice in the information technology sector

INFO5992
Understanding IT Innovations
6	P 24 credit points of units at 5000-level or above
N PMGT5875 OR OINF5992
Data Science Specialist units of study
COMP5046
Natural Language Processing	6	A Knowledge of an OO programming language
N COMP4446
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
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).
N COMP4318 OR OCMP5318
COMP5328
Advanced Machine Learning	6	C COMP5318 OR COMP4318 OR COMP3308 OR COMP3608
N COMP4328 OR OCMP5328
COMP5329
Deep Learning	6	A COMP4318 OR COMP5318
N COMP4329 OR OCMP5329
COMP5338
Advanced Data Models	6	A This unit of study assumes foundational knowledge of relational database systems as taught in COMP5138/COMP9120 (Database Management Systems) or INFO2120/INFO2820/ISYS2120 (Database Systems 1)
N COMP4338 OR OCMP5338
COMP5339
Data Engineering	6	A Proficiency in programming, especially Python, and in database querying with SQL; basic Unix scripting
P COMP5310
N OCMP5339
COMP5349
Cloud Computing	6	A Basic programming skills as covered in INFO1110 or INFO1910 or ENGG1810 or COMP9001 or COMP9003. Knowledge of OS concepts as covered in INFO1112 or COMP9201 or COMP9601 would be an advantage.
N COMP4349 OR OCMP5349
COMP5425
Multimedia Retrieval	6	A Experience with programming skills, as covered in COMP9103 OR COMP9003 OR COMP9123 OR COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions)
N COMP4425
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)
QBUS6810
Statistical Learning and Data Mining	6	P (ECMT5001 or QBUS5001 or STAT5003) and (a mark of 65 or greater in BUSS6002 or COMP5310 or COMP5318)
Students should complete BUSS6002 before enrolling in this unit as QBUS6810 builds on the material covered in BUSS6002.
QBUS6840
Predictive Analytics	6	P (QBUS5001 or ECMT5001 or STAT5003) and (a mark of 65 or greater in BUSS6002 or COMP5310 or COMP5318)
Foundation units of study
COMP9001
Introduction to Programming
6	N INFO1110 OR INFO1910 OR INFO1103 OR INFO1903 OR INFO1105 OR INFO1905 OR ENGG1810
COMP9017
Systems Programming
6	A COMP9003
N COMP2129 OR COMP2017 OR COMP9129
COMP9110
System Analysis and Modelling
6	A Experience with a data model as in COMP9129 or COMP9103 or COMP9003 or COMP9220 or COMP9120 or COMP5212 or COMP5214 or COMP5028 or COMP5138
N ELEC3610 OR ELEC5743 OR INFO2110 OR INFO5001 OR ISYS2110
COMP9120
Database Management Systems
6	A Some exposure to programming and some familiarity with data model concepts
N INFO2120 OR INFO2820 OR INFO2005 OR INFO2905 OR COMP5138 OR ISYS2120. Students who have previously studied an introductory database subject as part of their undergraduate degree should not enrol in this foundational unit, as it covers the same foundational content
COMP9121
Design of Networks and Distributed Systems
6	N COMP5116
INFO6007
Project Management in IT
6	A Students enrolled in INFO6007 are assumed to have previously completed a Bachelor's degree in some area of IT, or have completed a Graduate Diploma in some area of IT, or have three years experience as a practising IT professional. Recent work experience, or recent postgraduate education, in software project management, software process improvement, or software quality assurance is an advantage
N PMGT5871
STAT5002
Introduction to Statistics	6	A HSC Mathematics
Elective units of study
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
COMP5216
Mobile Computing
6	A COMP5214 OR COMP9103 OR COMP9003. Software Development in JAVA, or similar introductory software development units
N COMP4216
COMP5347
Web Application Development
6	A Experience with software development as covered in SOFT2412 or COMP9103 or COMP9003 (or equivalent UoS from different institutions)
P INFO1103 or INFO1113 or COMP9103 or COMP9003 or COMP9220 or COMP5028
N COMP4347
COMP5348
Enterprise Scale Software Architecture	6	A Experience with software development as covered in SOFT2412 or COMP9103 and also COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions).
COMP5416
Advanced Network Technologies	6	A COMP3221 OR ELEC3506 OR ELEC9506 OR ELEC5740 OR COMP5116 OR COMP9121
N COMP4416
COMP5425
Multimedia Retrieval
6	A Experience with programming skills, as covered in COMP9103 OR COMP9003 OR COMP9123 OR COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions)
N COMP4425
COMP5426
Parallel and Distributed Computing
6	A Experience with algorithm design and software development as covered in (COMP2017 or COMP9017) and COMP3027 (or equivalent UoS from different institutions)
N COMP4426 OR OCMP5426
COMP5427
Usability Engineering	6	N COMP4427
CSYS5010
Introduction to Complex Systems	6	 
DATA5207
Data Analysis in the Social Sciences	6	N DATA4207
ELEC5514
IoT Wireless Sensing and Networking
6	A ELEC3305 AND ELEC3506 AND ELEC3607 AND ELEC5508
ELEC5517
Software Defined Networks	6	A ELEC3506 OR ELEC9506
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
PHYS5033
Environmental Footprints and IO Analysis	6	 
Capstone Project units of study
DATA5703
Data Science Capstone Project
12	P A candidate for the MDS who has completed 24 credit points from Core or Elective units of study may take this unit
N DATA5707 or DATA5708 or DATA5709
DATA5707
Data Science Capstone A
6	P A part-time enrolled candidate for the MDS who has completed 24 credit points from Core or Elective units of study may take this unit
N DATA5703 or DATA5709. Eligible students of the Data Science Capstone Project may choose either DATA5703 or (DATA5707 and DATA5708) or DATA5709
DATA5708
Data Science Capstone B
6	P A part-time enrolled candidate for the MDS who has completed 24 credit points from Core or Elective units of study may take this unit
C DATA5707
N DATA5703 or DATA5709. Eligible students of the Data Science Capstone Project may choose either DATA5703 or (DATA5707 and DATA5708) or DATA5709
DATA5709
Data Science Capstone Project - Individual	12	P A candidate for the MDS who has completed 24 credit points from Core or Elective units of study, and has a WAM of 75+ may take this unit
N DATA5703 or DATA5707 or DATA5708
Students are required to source for a project and an academic supervisor prior to enrolment.
Research Pathway units of study
DATA5702
Data Science Research Project A	12	A Students should take INFO5993 either concurrently or prior to undertaking this project unit
P 12cp of Data Science Core and 12cp of (Specialisation Core or Data Science Specialist) units of study
N DATA5703 or DATA5707 or DATA5708 or DATA5709
DATA5704
Data Science Research Project B	6	A Students should take INFO5993 either concurrently or prior to undertaking this project unit
P 12cp of Data Science Core and 12cp of (Specialisation Core or Data Science Specialist) units of study
N DATA5703 or DATA5707 or DATA5708 or DATA5709
INFO5993 Research Methods	6	 
Specialisations for the Master of Data Science
A Specialisation requires the completion of 18 credit points of Specialisation Core units of study as defined in the tables below.
Data Engineering specialisation
Specialisation core units of study
COMP5338
Advanced Data Models	6	A This unit of study assumes foundational knowledge of relational database systems as taught in COMP5138/COMP9120 (Database Management Systems) or INFO2120/INFO2820/ISYS2120 (Database Systems 1)
N COMP4338 OR OCMP5338
COMP5339
Data Engineering
6	A Proficiency in programming, especially Python, and in database querying with SQL; basic Unix scripting
P COMP5310
N OCMP5339
COMP5349
Cloud Computing	6	A Basic programming skills as covered in INFO1110 or INFO1910 or ENGG1810 or COMP9001 or COMP9003. Knowledge of OS concepts as covered in INFO1112 or COMP9201 or COMP9601 would be an advantage.
N COMP4349 OR OCMP5349
Machine Learning specialisation
Specialisation core units of study
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).
N COMP4318 OR OCMP5318
COMP5328
Advanced Machine Learning	6	C COMP5318 OR COMP4318 OR COMP3308 OR COMP3608
N COMP4328 OR OCMP5328
COMP5329
Deep Learning	6	A COMP4318 OR COMP5318
N COMP4329 OR OCMP5329
Unspecified specialisation
Unspecified Specialisation requires the completion of 18 credit points from the Data Science Specialist units of study table.