Faculty notice: this unit is changing
Final offering S1 2027
BCS - Data science and artificial intelligence, Data science
Replace with FIT3231 from S2 2027 (S1 and S2)
From: Re-enrolment and unit changes - Information Technology (undergraduate) · Last checked: 7 Oct 2026 UTC
Official wording from the faculty, shown as published. It is the page of the Faculty of IT on monash.edu, so confirm with your faculty that it applies to your campus and intake year. Replacements are decided by the faculty, not by this site.
Units / FIT3164
FIT3164 · Data science project 2
2027 Handbook6 credit pointsLevel 3Faculty of Information Technology
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
| Campus | Teaching period | Mode |
|---|---|---|
| Clayton | First semester | Activities scheduled as a mix of on-campus and online activities (BLENDED) |
| Malaysia | First semester | Teaching activities are on-campus (ON-CAMPUS) |
| Malaysia | Second semester | Teaching 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.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Individual Vlog Reflections | Artefact | 10% | — |
| 2 | Group Project Meeting Minutes & Videos | Written | 15% | — |
| 3 | Group Mid-Semester Project Pitch | Presentation | 25% | — |
| 4 | Individual Critique of Other Group Pitches | Demonstration | 5% | — |
| 5 | Individual Critique of Other Final Presentations | Demonstration | 5% | — |
| 6 | Software Demonstration and Final Presentation | Presentation | 30% | — |
| 7 | Final Written Report | Project | 10% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
Learning outcomes
- Evaluate and select research methods and techniques of data preparation and analysis appropriate to a particular project;
- Search, access, and analyse research literature as part of the process of developing solutions to problems;
- Work effectively in collaborative teams;
- Develop and test a substantial piece of software or perform a substantial analysis of data using software;
- Explain and reflect upon the purpose, operation, success and value of the developed project in writing and orally;
- 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.
| Activity | Duration |
|---|---|
| Studio activities | 36 hours |
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