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FIT3164 · Data science project 2

Official Handbook

2026 Handbook6 credit pointsLevel 3Faculty of Information Technology

Last checked: 23 Aug 2026 UTC

Overview

This unit provides practical experience in researching, designing, developing and testing a non-trivial data science project. Projects involve whole or part of the data science process (visualisation, analysis, algorithms, etc.) but can also be software-based, or they may involve investigation of theory. Projects if software-based should cover analysis through design to implementation and testing. Comprehensive written documentation on the project is required. Students are assigned in groups to a project supervisor. There are no lectures in this unit, although you will be expected to attend regular meetings with your project supervisor. The unit is the second part of a 12-credit point project sequence; the first part and entry point for the project is FIT3163.

Offerings

CampusTeaching periodMode
MalaysiaFirst semesterTeaching activities are on-campus (ON-CAMPUS)
MalaysiaSecond semesterTeaching activities are on-campus (ON-CAMPUS)
ClaytonFirst semesterTeaching activities are on-campus (ON-CAMPUS)
MalaysiaSummer semester ATeaching activities are on-campus (ON-CAMPUS)
ClaytonSecond semesterTeaching activities are on-campus (ON-CAMPUS)

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

#AssessmentTypeWeightHurdle
1Individual Vlog ReflectionsArtefact10%
2Group Project Meeting Minutes & VideosWritten15%
3Group Mid-Semester Project PitchPresentation25%
4Individual Critique of Other Group PitchesDemonstration5%
5Individual Critique of Other Final PresentationsDemonstration5%
6Software Demonstration and Final PresentationPresentation30%
7Final Written ReportProject10%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

prohibitions

  • FIT3144 — Advanced computer science research project

prerequisite

Learning outcomes

  1. Evaluate and select research methods and techniques of data preparation and analysis appropriate to a particular project;
  2. Search, access, and analyse research literature as part of the process of developing solutions to problems;
  3. Work effectively in collaborative teams;
  4. Develop and test a substantial piece of software or perform a substantial analysis of data using software;
  5. Explain and reflect upon the purpose, operation, success and value of the developed project in writing and orally;
  6. Write a report explaining methodology, outlining their contributions and the contributions of others, and documenting the developed project from appropriate perspectives, for instance that of a user, researcher or developer.

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.

ActivityDuration
Studio activities36 hours

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