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HE Unit Template
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Data Science for All
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ITECH5007 - Data Science for All
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20240200
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Course
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1.2
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2026-09-10
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2026-09-10
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Information Technology
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Institute of Innovation, Science & Sustainability
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Information Technology
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Postgraduate - Coursework
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15
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.125
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020199
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Computer Science, n.e.c.
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020199 - Computer Science, n.e.c.
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<a href="http://www.federation.edu.au/locate/unit/itech5007">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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<p>DATA SCIENCE FOR ALL is an introductory unit to data science, a fast-growing and exciting field. This unit will provide an overview of a number of topics that play fundamental roles across various subjects in data science. The unit features an emphasis on foundations and practical knowledge of data science, as well as computational thinking and real-world relevance. Topics to be covered include data types, data representation, data preparation, data processing and mining, data management, data exploration and visualisation. Hands-on experience working with real-world data, techniques, and tools will prepare students for advanced units and enable students to start careers as data scientists.</p>
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<p>Topics may include: introduction to data and data science data types and representation foundations of algorithms and programming data collection, pre-processing, and wrangling data visualisation data management data analytics fundamentals of data mining data science tools</p>
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<p>Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment.</p>
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0200
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Year
2027
Current Year
2026
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ITECH5007 - Data Science for All
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ITECH5007 - Data Science for All
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Semester
Semester 1
Semester 2
Summer Semester
Year
2027
2026
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Overview
Key information
Requisites
Learning outcomes
Assessment
FedTASK
Parent Region
Overview
Unit description
<p>DATA SCIENCE FOR ALL is an introductory unit to data science, a fast-growing and exciting field. This unit will provide an overview of a number of topics that play fundamental roles across various subjects in data science. The unit features an emphasis on foundations and practical knowledge of data science, as well as computational thinking and real-world relevance. Topics to be covered include data types, data representation, data preparation, data processing and mining, data management, data exploration and visualisation. Hands-on experience working with real-world data, techniques, and tools will prepare students for advanced units and enable students to start careers as data scientists.</p>
Unit content
<p>Topics may include: introduction to data and data science data types and representation foundations of algorithms and programming data collection, pre-processing, and wrangling data visualisation data management data analytics fundamentals of data mining data science tools</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Postgraduate - Coursework
Credit points:
15
EFTSL:
0.125
Field of education:
020199 - Computer Science, 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/itech5007">View unit fees</a>
Requisites
Prerequisite
None
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>Interpret the principles of modern data science as well as data science lifecycle.</p>
K2
<p>Differentiate between the most common forms of data types and representations.</p>
K3
<p>Critique and apply a core collection of elementary techniques for data preparation, processing, management, exploration, and visualisation.</p>
K4
<p>Examine a core collection of methods and algorithms for data analysis and mining.</p>
S1
<p>Demonstrate competent skills in using data science technology for solving complex problems at an appropriate level of difficulty.</p>
S2
<p>Contrast and use data science software and tools.</p>
S3
<p>Implement any chosen data science solution and communicate the results effectively.</p>
A1
<p>Employ appropriate techniques and tools to process and analyse data.</p>
A2
<p>Integrate data science principles, methods, techniques and tools covered in this unit to plan and execute a data science project.</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>Students will apply data science principles, methods, techniques and tools to design, implement and document solutions to simple problems.</p>
<p>Assignments and exercises</p>
<p>40%-50%</p>
S1, S2, S3, A1, A2
2
<p>Students will provide theoretical answers and provide practical solutions to a range of questions and problems drawn from theory and examples used during the unit.</p>
<p>Test(s)</p>
<p>50%-60%</p>
K1, K2, K3, K4, S1, S2, S3, A1
Supplementary assessment available:
Yes
Supplementary assessment information:
<p>Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment.</p>
FedTASK
FedTASK
<p>Federation University recognises that students require key transferable employability skills to prepare them for their future workplace and society. FedTASKs (<strong>T</strong>ransferable <strong>A</strong>ttributes <strong>S</strong>kills and <strong>K</strong>nowledge) provide a targeted focus on five key, transferable Attributes, Skills, and Knowledge that are embedded within curriculum, developed gradually towards successful measures and interlinked with cross-discipline and co-operative learning opportunities.</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Postgraduate - Coursework
Credit points:
15
EFTSL:
0.125
Field of education:
020199 - Computer Science, 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/itech5007">View unit fees</a>
Additional information
Add Info Static Text
Internal reference: ITECH5007 - U1.2