Data Science minor

The ability to understand and critically evaluate the assumptions which underlie data and its presentation are invaluable. A solid grasp of data science offers a key pathway to success in a broad range of careers across all sectors of endeavour. The Minor in Data Science provides a grounding in statistics, data analysis and computational thinking and is suitable for students in both non-STEM and STEM related fields.

Outcomes

Students are able to (1) critically assess the application and outcome of Data Science workflow to a problem; (2) select the appropriate statistical techniques for use in particular real-world settings
; (3) apply statistical techniques to data analysis using computational methods; (4) devise and implement computational models and simple numerical methods in a modern programming language; and (5) demonstrate the power of statistical concepts in the interpretation of data.

Unit sequence

Key to availability of units:
S1 = Semester 1; S2 = Semester 2
Take all units (12 points):
Availability Unit code Unit name Unit requirements
S1, S2 CITS1401 Computational Thinking with Python
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
S1, S2 STAT1400 Statistics for Science
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
STAT1520 Economic and Business Statistics
Take the following unit:
Availability Unit code Unit name Unit requirements
S2 CITS2402 Introduction to Data Science
Prerequisites:
CITS1401 Computational Thinking with Python
or
CITS2401 Computer Analysis and Visualisation
Take unit(s) to the value of 6 points:
Availability Unit code Unit name Unit requirements
S1 STAT2401 Analysis of Experiments
S2 STAT2402 Analysis of Observations