SIT742 - Modern Data Science

Year:

2020 unit information

Enrolment modes: Trimester 1: Burwood (Melbourne), Cloud (online)
Credit point(s): 1
EFTSL value: 0.125
Prerequisite:

Nil

Corequisite:

Nil

Incompatible with:

Nil

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 class per week, 1 x 1 hour practical per week.

Scheduled learning activities - cloud (online)

1 x 1 hour scheduled online workshop per week.

Content

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

Click on the fee link below which describes you:

Talk to a Deakin adviser about studying at Deakin today

Call 1800 693 888Monday to Friday: 9am to 5pm AEDT
Chat live nowMonday to Friday: 8am to 7pm AEDT