UnitLevel 3Undergraduate

FIT3220 Data science in practice: Project 1

Faculty of Information Technology

FIT3220 Data science in practice: Project 1 is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology. It isn't offered in 2027. It needs FIT2136; or (FIT2135 and FIT2086) and unlocks 1 unit, leading on to 3 units in all.

Credit points
6
Offered in 2027
Not offered

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Requisites

Overview

This unit is the third stage of the Data Science practice program. You will continue working within a student-led company, contributing to real projects, products or services that use data to support insight, modelling, communication or decision-making. Building on earlier practice units, you will take greater responsibility for data-focused work while continuing to operate within team, project and company expectations.

At this stage, you will also help sustain the company by supporting recruitment and onboarding of students entering the first practice unit. You may help define role needs, review applicant evidence, support interviews or selection activities, and induct new students into company data practices, workflows, tools and professional expectations.

You will take greater agency over your professional and academic development by identifying the data science capabilities you want to strengthen. In consultation with mentors, peers and company leaders, you will set development goals, seek feedback, and build portfolio evidence of your growing capability. Your work may involve acquiring, preparing, analysing, modelling, visualising or communicating data, while considering data quality, uncertainty, bias, interpretation, governance and responsible use.

Assessment is centred on an individual evidence-based portfolio demonstrating your contribution to company work, support for new students, response to feedback, and advancing data science capability. This unit prepares you for the capstone practice unit, where you will be expected to demonstrate more independent and integrated data science practice in complex professional contexts.

Offerings in 2027

The 2027 handbook lists no offerings for FIT3220.

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Direct your professional and academic development by identifying capability goals, seeking and responding to feedback, supporting recruitment and onboarding activities, and evidencing growth through reflective practice;

  2. 2

    Design and apply data science workflows that support acquisition, preparation, analysis, modelling, interpretation or evaluation of data in a company project context;

  3. 3

    Develop and evaluate data visualisations, dashboards or data stories that communicate patterns, uncertainty, limitations and insights to relevant audiences;

  4. 4

    Contribute to the development, evaluation or interpretation of machine learning models or model-enabled workflows, using appropriate evidence and performance measures;

  5. 5

    Demonstrate advancing Data Science course capability through portfolio evidence of individual contribution, analytical reasoning, technical decision-making, feedback response and professional judgement.

Common questions

What are the prerequisites for FIT3220?

You need FIT2136; or (FIT2135 and FIT2086) before you enrol.

What can I take after FIT3220?

FIT3220 is a prerequisite or corequisite for 1 unit, including FIT3221. Those lead on to 3 units in all.

When is FIT3220 offered?

FIT3220 has no offerings listed in the 2027 handbook.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Information Technology
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Available
Handbook years
2027