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HE Unit Template
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Mathematics for Data Science
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MATHS5000 - Mathematics for Data Science
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20260100
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Course
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Unit
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2.2
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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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Undergraduate
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15
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.125
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010101
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Mathematics
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010101 - Mathematics
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<a href="http://www.federation.edu.au/locate/unit/maths5000">View unit fees</a>
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Graded (e.g. HD, D, C, etc)
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Bachelor Honours Degree, Graduate Certificate, Graduate Diploma
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Introductory
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<p>This unit covers key mathematical concepts relevant to Data Science and related fields such as Software Engineering. Students are provided with a foundation of mathematics required for further study, including vectors, systems of linear equations, linear programming, set theory, calculus, and probability theory. Students explore the utility of these tools through application to real-world problems.</p>
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<p>Topics may include:<br>
1. Gradients, Derivatives, and Global and Local Minima/Maxima<br>
2. Introduction to Vectors, Lines, and Planes in nD space<br>
3. Systems of Linear Equations<br>
4. Matrix Arithmetic<br>
5. Determinants, Inverses, Eigenvalues, and Eigenvectors<br>
6. Graphical Representations of Linear Programming Problems<br>
7. Foundational set theory<br>
8. Random Variables and Probability Distributions<br>
9. Markov chains and conditional probability<br>
10. Stochastic processes and probabilistic modelling</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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Year
Year
2027
Current Year
2026
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MATHS5000 - Mathematics for Data Science
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MATHS5000 - Mathematics for Data Science
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Semester
Semester 1
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 covers key mathematical concepts relevant to Data Science and related fields such as Software Engineering. Students are provided with a foundation of mathematics required for further study, including vectors, systems of linear equations, linear programming, set theory, calculus, and probability theory. Students explore the utility of these tools through application to real-world problems.</p>
Unit content
<p>Topics may include:<br> 1. Gradients, Derivatives, and Global and Local Minima/Maxima<br> 2. Introduction to Vectors, Lines, and Planes in nD space<br> 3. Systems of Linear Equations<br> 4. Matrix Arithmetic<br> 5. Determinants, Inverses, Eigenvalues, and Eigenvectors<br> 6. Graphical Representations of Linear Programming Problems<br> 7. Foundational set theory<br> 8. Random Variables and Probability Distributions<br> 9. Markov chains and conditional probability<br> 10. Stochastic processes and probabilistic modelling</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Engineering
Study level:
Undergraduate
Credit points:
15
EFTSL:
0.125
Field of education:
010101 - Mathematics
Offering:
<p><strong>Semester 1</strong><p>Ballarat - Mt Helen (On Campus)</p><p>Melbourne City Campus (On Campus)</p><p>On-line Learning</p></p>
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/maths5000">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>Describe the nature of vectors, lines, and planes in nD-space.</p>
K2
<p>Analyze and solve systems of linear equations relevant to data science and software engineering problems.</p>
K3
<p>Explain the principles of probability theory, including random variables, probability distributions, conditional probability, Markov chains, and stochastic processes.</p>
K4
<p>Describe the relationships between functions, derivatives, gradients, maxima, and minima</p>
S1
<p>Evaluate and apply matrix arithmetic, including the calculation of determinants, inverses, eigenvalues, and eigenvectors.</p>
S2
<p>Create and interpret graphical representations of linear programming problems in two dimensions.</p>
S3
<p>Apply appropriate algorithms to solve complex problems in linear programming.</p>
S4
<p>Apply appropriate algorithms to probabilistic modelling.</p>
S5
<p>Express mathematical structures using set theory</p>
A1
<p>Synthesize knowledge of linear equations, matrices, vectors, linear programming, and probability to solve real-world problems in data science and software engineering.</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>Analyze and solve a system of linear equations relevant to a given data science problem. Create and interpret a graphical representation of a two-dimensional linear programming problem.</p>
<p>Report and/or Presentation</p>
<p>20% - 30%</p>
K1, K2, S1, S2, S3, A1
2
<p>Present solutions to a set of problems related to unit contents. Explain the meaning of findings for both specialist and mainstream audiences.</p>
<p>Tutorial tasks</p>
<p>30% - 50%</p>
K1, K2, K3, K4, S1, S2, S3, S4, S5, A1
3
<p>Complete an exam or test</p>
<p>Exam/test</p>
<p>30% - 50%</p>
K1, K2, K3, K4, S1, S4, S5
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>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Engineering
Study level:
Undergraduate
Credit points:
15
EFTSL:
0.125
Field of education:
010101 - Mathematics
Offering:
<p><strong>Semester 1</strong><p>Ballarat - Mt Helen (On Campus)</p><p>Melbourne City Campus (On Campus)</p><p>On-line Learning</p></p>
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/maths5000">View unit fees</a>
Additional information
Add Info Static Text
Internal reference: MATHS5000 - U2.2