SIG742 - Modern Data Science
| Year: | 2025 unit information |
|---|---|
| Enrolment modes: | Trimester 2: Great Learning |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Prerequisite: | Nil |
| Corequisite: | Must be enrolled in S773 Master of Data Science (Global) |
| Incompatible with: | SIT742 |
| Study commitment | Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit. This will include educator guided online learning activities within the unit site. |
| Scheduled learning activities - online | Online independent and collaborative learning including optional scheduled activities as detailed via the Great Learning platform. |
| Note: | This unit is part of the Master of Data Science (Global) program and is restricted to online international students who reside outside Australia. |
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.