SIT742 - Modern Data Science


2023 unit information

Enrolment modes: Trimester 2: Burwood (Melbourne), Online
Credit point(s): 1
EFTSL value: 0.125




Incompatible with:


Study commitment

Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.

Scheduled learning activities - campus

1 x 2 hour online class per week, 1 x 2 hour workshop per week. Weekly drop-in sessions.

Scheduled learning activities - cloud (online)

Online independent and collaborative learning including optional scheduled activities as detailed in the unit site.


In this unit, students will have the opportunity to learn fundamental aspects of data science, modern methods, techniques and applications of data science. Upon successful completion of study, students will be able to use distributed storage and computing platform to process and analyse big data, and use modern techniques in data analytics.

Learning activities in this unit are designed for students to develop knowledge and skills in reviewing tabular data such as relational database, distributed storage and computing platforms with materials on Apache Spark. In learning data analytics, students will use feature selection, data reduction and machine learning methods. Students will also have the opportunity to learn advanced concepts in prediction including linear regression, logistic regression and decision tree classifiers, and to learn frequent pattern discovery using association rule mining algorithms.

Unit Fee Information

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