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Master of Data Science (MC-DATASC) // Subject options

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Subject options

*‘Prerequisite’ Subjects (up to 50 points depending on educational background)

It is expected that students admitted into the course will have either computer science or statistics background, though some students may have a mix of both.

  • If a student has a computer science background, they will be required to complete statistics subjects in their first year as part of their elective component to satisfy the prerequsites for the Statistics core subjects
  • If the student has Statistics background, they will need to complete computer science subjects in their first year as part of their elective component to satisfy the prerequsites for the Computer Science core subjects
  • If a student already meets the prerequisites for the core subejcts, they can choose their elective subjects freely.

Dependant upon educational background students may need to take up to 50 points of the following:

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Student entering with a Computer Science background may need to take

Code Name Study period Credit Points
MAST90105 Methods of Mathematical Statistics
Semester 1
25
MAST90104 A First Course In Statistical Learning
Semester 2
25

Student entering with a Statistics background may need to take:

Code Name Study period Credit Points
COMP90041 Programming and Software Development
Semester 1
Semester 2
12.5
COMP90038 Algorithms and Complexity
Semester 1
Semester 2
12.5
COMP90049 Knowledge Technologies
Semester 1
Semester 2
12.5
INFO90002 Database Systems & Information Modelling
Semester 1
Semester 2
12.5

Core (125 points):

Students must take:

Statistics core subjects

Code Name Study period Credit Points
MAST90082 Mathematical Statistics
Semester 1
12.5
MAST90084 Statistical Modelling
Semester 1
12.5
MAST90083 Computational Statistics and Data Mining
Semester 2
12.5
MAST90085 Multivariate Statistical Techniques
Semester 2
12.5

Computer Science core subjects

Code Name Study period Credit Points
COMP90024 Cluster and Cloud Computing
Semester 1
12.5
COMP90042 Web Search and Text Analysis
Semester 1
12.5
COMP90051 Statistical Machine Learning
Semester 2
12.5
COMP90050 Advanced Database Systems
Semester 1
12.5

Capstone Project

Students are expected to have completed at least two semesters of their course before beginning the Data Science Project

Code Name Study period Credit Points
MAST90106 Data Science Project Pt1
Semester 1
Semester 2
12.5
MAST90107 Data Science Project Pt2
Semester 1
Semester 2
12.5

Electives (50-75 points):

The remainder of the 200 points are made up subjects that may include Prerequisite Subjects (maximum 50 points, listed above), Discipline Elective Subjects, Professional Skills Subjects (maximum 25 pts) and an optional Data Science Research Project.

Discipline Elective Subjects

Code Name Study period Credit Points
GEOM90008 Foundations of Spatial Information
Semester 1
Semester 2
12.5
GEOM90018 Spatial Databases
Semester 1
12.5
GEOM90006 Spatial Analysis
Semester 2
12.5
GEOM90007 Spatial Visualisation
Semester 2
12.5
MAST90110 Analysis of High-Dimensional Data
Semester 2
12.5
MAST90111 Advanced Statistical Modelling Not available in 2017 12.5
MAST90051 Mathematics of Risk Not available in 2017 12.5
MAST90014 Optimisation for Industry
Semester 1
12.5
MAST90027 The Practice of Statistics Not available in 2017 12.5
MAST90059 Stochastic Calculus with Applications
Semester 1
12.5
MAST90081 Advanced Probability
Semester 1
12.5
MAST90019 Random Processes
Semester 2
12.5
COMP90054 AI Planning for Autonomy
Semester 2
12.5
COMP90057 Advanced Theoretical Computer Science
Semester 2
12.5
COMP90014 Algorithms for Functional Genomics
Semester 2
12.5
COMP90016 Computational Genomics
Semester 1
12.5
COMP90046 Constraint Programming
Semester 2
12.5
COMP90043 Cryptography and Security
Semester 2
12.5
COMP90048 Declarative Programming
Semester 2
12.5
COMP90020 Distributed Algorithms
Semester 1
12.5
COMP90015 Distributed Systems
Semester 1
Semester 2
12.5
COMP90007 Internet Technologies
Semester 1
Semester 2
12.5
COMP90018 Mobile Computing Systems Programming
Semester 2
12.5
COMP90025 Parallel and Multicore Computing
Semester 2
12.5
COMP90045 Programming Language Implementation
Semester 1
12.5
COMP90042 Web Search and Text Analysis
Semester 1
12.5
ISYS90035 Knowledge Management Systems
Semester 1
12.5
ISYS90086 Data Warehousing
Summer Term
12.5

Professional Skills Subjects

Students may take no more than 25 points of the following:

Code Name Study period Credit Points
SCIE90012 Science Communication
Semester 2
12.5
SCIE90013 Communication for Research Scientists
Semester 1
12.5
EDUC90839 Science in Schools
Semester 1
12.5
SCIE90017 Science and Technology Internship
Summer Term
Semester 1
Semester 2
12.5

Data Science Research Project

Students who maintain a sufficiently high weighted average mark will be eligible to undertake a 25 point individual research project in Data Science:

Code Name Study period Credit Points
MAST90108 Data Science Research Project Pt1
Semester 1
Semester 2
12.5
MAST90109 Data Science Research Project Pt2
Semester 1
Semester 2
12.5

Students must first have agreement from a supervisor before enrolling in the research project.

Last updated: 04 August 2017