UnitLevel 2Undergraduate

MTH2019 Multivariate mathematics for data science

Faculty of Science

MTH2019 Multivariate mathematics for data science is a level 2, 6-credit-point, undergraduate unit from the Faculty of Science, offered in 2021 in Semester 1 at Clayton. It has no prerequisites and unlocks 5 units, leading on to 32 units in all.

Credit points
6
Offered in 2021
Semester 1
Clayton
Assessment
Exam 60%
and 1 other task

This is the 2021 handbook entry. See the 2027 entry.

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Requisites

Overview

This unit introduces and develops a range of basic concepts and techniques related to two main subjects: multivariate calculus and linear algebra. The programme is targeted for students following a degree in data science and the material will have emphasis on assimilating important principles, on developing classical techniques, and on facilitating the use of the theoretical framework and practical methods in the context of common applicative problems. The unit will cover partial derivatives, extrema of multivariate functions, integration, linear transformations, matrices and orthogonalisation, eigenvalues and eigenvectors, and applications to data science.

Offerings in 2021

Teaching periodCampusMode
First semesterClaytonOn campus

Assessment

  • Continuous assessmentOtherThreshold hurdle
    40%
  • Examination (3 hours and 10 minutes)ExamThreshold hurdle
    60%

Learning outcomes

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

  1. 1

    Successfully describe, and apply multivariate mathematics to problems in data science;

  2. 2

    Exhibit key skills in the calculus of functions of several variables including the computation of partial derivatives, finding tangent planes and identifying stationary points, root finding, and convexity for optimisation;

  3. 3

    Compute line, surface and volume integrals in a range of coordinate systems;

  4. 4

    Demonstrate their comprehension of basic concepts related to linear transformations and vector spaces, including subspace, span, linear independence, basis, kernel and range;

  5. 5

    Diagonalise real matrices by computing their eigenvalues and finding their eigenspaces;

  6. 6

    Explain and apply basic concepts related to inner product spaces to problems such as least-squares data fitting;

  7. 7

    Use appropriate technology (e.g. computer algebra packages) to solve certain classes of mathematical problems;

  8. 8

    Present clear mathematical arguments in written and oral form.

Workload and teaching

  • Workshops36 hours
  • Applied sessions16.5 hours
  • Three 1-hour lectures and
  • One 1.5-hour applied class per week (in weeks 2-12)

Contacts

Chief Examiners
Associate Professor Ricardo Ruiz Baier
Unit Coordinators
Associate Professor Ricardo Ruiz Baier

Common questions

What are the prerequisites for MTH2019?

MTH2019 has no prerequisites, but enrolment rules apply.

What can I take after MTH2019?

MTH2019 is a prerequisite or corequisite for 5 units, including MTH2051, MTH2222, MTH3241, MTH3320 and MTH3330. Those lead on to 32 units in all.

When is MTH2019 offered?

In 2021, MTH2019 runs in Semester 1 at Clayton.

Does MTH2019 have an exam?

Yes. The exam is worth 60% of the final mark, alongside 1 other task.

More details

Credit points
6
Level
2
Study level
Undergraduate
Faculty
Faculty of Science
Organisational unit
School of Mathematics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 1
Study abroad
Not available
Handbook years
2021202220232024202520262027