Minor Overview
 About this 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 nonSTEM and STEM related fields. For students taking a minor which shares units with their other unit sets (majors or minors): in order for minors to be recognised on academic and graduation documents, students may only have a maximum of one unit overlapping between their unit sets.
 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 realworld 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.  Incompatibility
MJDDATSC Data Science;
MJDCDSDM Computing and Data Science;
MNRASTAT Applied Statistical Learning
Units
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  
S1, S2  STAT1400  Statistics for Science 
Take the following unit:
Availability  Unit code  Unit name  Unit requirements 

S2  CITS2402  Introduction to Data Science 
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 
