Program Overview

Bachelor of Engineering Honours

The Bachelor of Engineering Honours program offers a Software Engineering stream with various specialisations, including Engineering Data Science.

Software Engineering Stream

The Software Engineering stream is designed to equip students with the skills and knowledge required to succeed in the field of software engineering.

Engineering Data Science Specialisation

The Engineering Data Science specialisation is a 30-credit-point program that focuses on the application of data science principles to engineering problems.

Requirements

To achieve this specialisation, students must complete 30 credit points, consisting of:

• 18 credit points from the following units:
  • DATA2001: Data Science, Big Data and Data Variety (6 credit points)
    • Prerequisites: DATA1002 or DATA1902 or INFO1110 or INFO1910 or INFO1903 or INFO1103 or ENGG1810
    • Prohibition: DATA2901
  • DATA2901: Big Data and Data Diversity (Advanced) (6 credit points)
    • Prerequisites: 75% or above from (DATA1002 or DATA1902 or INFO1110 or INFO1910 or INFO1903 or INFO1103 or ENGG1810)
    • Prohibition: DATA2001
  • DATA2002: Data Analytics: Learning from Data (6 credit points)
    • Assumed knowledge: Successful completion of a first-year or second-year unit in statistics or data science including a substantial coding component
    • Prerequisites: DATA1X01 or ENVX1002 or BUSS1020 or ECMT1010 or MATH1062 or MATH1962 or MATH1972 or [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)]
    • Prohibition: STAT2012 or STAT2912 or DATA2902
  • DATA2902: Data Analytics: Learning from Data (Adv) (6 credit points)
    • Assumed knowledge: Successful completion of a first-year or second-year unit in statistics or data science including a substantial coding component
    • Prerequisites: A mark of 65 or greater in (DATA1X01 or ENVX1002 or BUSS1020 or ECMT1010 or MATH1062 or MATH1962 or MATH1972 or [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)])
    • Prohibition: STAT2012 or STAT2912 or DATA2002
  • STAT2011: Probability and Estimation Theory (6 credit points)
    • Prerequisites: (MATH1X61 or MATH1971 or MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and (DATA1X01 or MATH1X62 or MATH1972 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020)
    • Prohibition: STAT2911
  • STAT2911: Probability and Statistical Models (Adv) (6 credit points)
    • Prerequisites: (MATH1X61 or MATH1971 or MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and a mark of 65 or greater in (DATA1X01 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020 or MATH1X62 or MATH1972)
    • Prohibition: STAT2011
• 12 credit points from the following units:
  • COMP3308: Introduction to Artificial Intelligence (6 credit points)
    • Assumed knowledge: Data structures and algorithms as covered in COMP2123 or COMP2823
    • Prerequisites: INFO1110 or INFO1910 or ENGG1801 or ENGG1810 or DATA1002 or DATA1902
    • Prohibition: COMP3608
  • COMP3608: Introduction to Artificial Intelligence (Adv) (6 credit points)
    • Assumed knowledge: Data structures and algorithms as covered in COMP2123 or COMP2823
    • Prerequisites: (INFO1110 or INFO1910 or ENGG1810 or DATA1002 or DATA1902) and distinction-level results in at least one 2000-level COMP or MATH or SOFT unit
    • Prohibition: COMP3308
  • DATA3404: Scalable Data Management (6 credit points)
    • Assumed knowledge: This unit of study assumes that students have previous knowledge of database structures and of SQL
    • Prerequisites: DATA2001 or DATA2901 or ISYS2120 or INFO2120 or INFO2820
    • Prohibition: INFO3504 or INFO3404
  • DATA3406: Human-in-the-Loop Data Analytics (6 credit points)
    • Assumed knowledge: Basic statistics, database management, and programming
    • Prerequisites: (DATA2001 or DATA2901) and (DATA2002 or DATA2902)