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HE Unit Template
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Advanced Data Science Project 1
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DATSC5001 - Advanced Data Science Project 1
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20250100
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Course
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Unit
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2.1
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2026-09-10
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2026-09-10
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Engineering
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Institute of Innovation, Science & Sustainability
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Engineering
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Postgraduate - Coursework
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30
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010199
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Mathematical Sciences, n.e.c.
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010199 - Mathematical Sciences, n.e.c.
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<a href="http://www.federation.edu.au/locate/unit/datsc5001">View unit fees</a>
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Graded (e.g. HD, D, C, etc)
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Masters Degree
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Advanced
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<p>This unit is intended to be taken in sequence with DATSC5002 and will equip you with the knowledge and skills to undertake an extensive data science research project. During the unit, you will be employing a combination of theoretical, analytical and computing skills relevant to your field of advanced study. In particular, you will critically review relevant literature and present your findings in front of a peer based audience.</p>
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<p>•This unit is designed to foster problem-based self learning and research. There will be minimal formal lectures.<br>
•Research ethics and principles<br>
•Types of scientific research<br>
•Research questions and hypotheses<br>
•Literature review<br>
•Data analysis methods and rationale<br>
•Communicating scientific results<br>
•Preparing scientific publications and thesis</p>
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Semester
Semester
0200
Year
Year
2027
Current Year
2026
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DATSC5001 - Advanced Data Science Project 1
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DATSC5001 - Advanced Data Science Project 1
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Semester 2
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Year
2027
2026
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Overview
Key information
Requisites
Learning outcomes
Assessment
Parent Region
Overview
Unit description
<p>This unit is intended to be taken in sequence with DATSC5002 and will equip you with the knowledge and skills to undertake an extensive data science research project. During the unit, you will be employing a combination of theoretical, analytical and computing skills relevant to your field of advanced study. In particular, you will critically review relevant literature and present your findings in front of a peer based audience.</p>
Unit content
<p>•This unit is designed to foster problem-based self learning and research. There will be minimal formal lectures.<br> •Research ethics and principles<br> •Types of scientific research<br> •Research questions and hypotheses<br> •Literature review<br> •Data analysis methods and rationale<br> •Communicating scientific results<br> •Preparing scientific publications and thesis</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Engineering
Study level:
Postgraduate - Coursework
Credit points:
30
EFTSL:
0.25
Field of education:
010199 - Mathematical Sciences, n.e.c.
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/datsc5001">View unit fees</a>
Requisites
Prerequisite
<p>must have completed "<a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH5500" target="_blank">ITECH5500</a>"</p>
Corequisite
None
Exclusion
None
Learning outcomes
Learning outcomes
<p>On successful completion of this unit, students are expected to gain the following [K]nowledge, [S]kills and [A]pplication of knowledge & skills</p>
Learning Outcomes
Ref
Outcome
K1
<p>Analyse the concepts underlying research in data science.</p>
K2
<p>Justify how to approach and undertake a research project.</p>
K3
<p>Apply critical thinking to research design and investigation.</p>
S1
<p>Apply mathematics, statistics and predictive modelling techniues to gain insights, predict behaviours and generate value from data.</p>
S2
<p>Communicate the outcomes of your research to peers through written and verbal means.</p>
S3
<p>Critically review and synthesize research literature.</p>
S4
<p>Construct appropriate research methodologies and evaluate their limitations.</p>
A1
<p>Assess and synthesize information from statistical data analysis.</p>
A2
<p>Produce a major piece of written work through a thesis (and other formats), commensurate with the discipline and field of research.</p>
A3
<p>Critique existing regression and multivariate methods in literature and recomend improvements, where appropriate, to create new knowledge.</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>Project proposal: A short concise project proposal (approx. 3 pages) clearly outlining the research plan to be undertaken as part of DATSC5001 and DATSC5002 units.</p>
<p>Report</p>
<p>5 - 15%</p>
K1, K2, K3, S3, A1, A3
2
<p>Mid-term progress presentation: Presentation demonstrating ongoing progress in your project tasks, particularly with reference to literature review, research gaps and methodology outlining clear descriptions of data analysis techniques.</p>
<p>Presentation</p>
<p>10 - 20%</p>
K1, K2, K3, S1, S2, S3, A1
3
<p>Final Report: A complete draft of a dissertation, technical report or an academic paper. This must include complete sections on literature review, data source and methodology and preliminary results.</p>
<p>Report</p>
<p>70-80%</p>
K1, K2, K3, S2, S4, A1, A3
Supplementary assessment available:
No
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Engineering
Study level:
Postgraduate - Coursework
Credit points:
30
EFTSL:
0.25
Field of education:
010199 - Mathematical Sciences, n.e.c.
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/datsc5001">View unit fees</a>
Additional information
Cards Section - Non Research
Add Info Static Text
Internal reference: DATSC5001 - U2.1