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UnitLevel 3Undergraduate

MMA3001 Numerical methods and machine learning

Faculty of Engineering

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MMA3001 Numerical methods and machine learning is a level 3, 6-credit-point, undergraduate unit from the Faculty of Engineering, offered in 2026 in Semester 2 at Clayton and Malaysia. It needs ENG2005 and (ENG1014 or ENG1060) and unlocks 1 unit.

Credit points
6
Offered in 2026
Semester 2
Clayton, Malaysia
Assessment
No exam
5 tasks
Workload
144 hours
per semester

This is the 2026 handbook entry. See the 2027 entry.

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Requisites

Before MMA3001

Prerequisites

Pass these before you enrol.

All of
One of

Prohibitions

You can't enrol if you have passed any of these.

One of

After MMA3001

1 unit list MMA3001 as a prerequisite or corequisite.

Overview

This unit conveys the fundamentals of numerical analysis techniques and their application to data analysis and the
solution of engineering problems. You will be introduced to programming structures, use of AI in programing, software documentation, version control and data management, profiling and hardware optimisation, conventions of scientific computing, numerical errors and stability, techniques for interpolation, integration, the solution of ordinary and partial differential equations, and principles of machine learning.

Offerings in 2026

Teaching periodCampusMode
Second semesterClaytonFlexible
Second semesterMalaysiaOn campus

Assessment

  • In-class test 1Quiz / Test
    25%
  • In-class test 2Quiz / Test
    25%
  • In-class test 3Quiz / Test
    25%
  • Project submissionProject
    25%
  • Life-long learning demonstrationWrittenCompetency hurdle
    -

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Learning outcomes

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

  1. 1

    Assess the suitability and limitations of machine learning for current and emerging engineering applications, demonstrating awareness of future directions in engineering practice.

  2. 2

    Demonstrate effective use of numerical analysis and machine learning tools to develop defensible solutions to open-ended engineering problems.

  3. 3

    Apply appropriate mathematical and numerical techniques to solve common engineering problems, and evaluate program performance, error, stability, and accuracy.

Workload and teaching

  • Workshops24 hours
  • Practical activities24 hours
  • Teaching approachActive learning
  • Teaching approachProblem-based learning

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

You will actively engage in applying your knowledge, skills, and attributes in interactive,  collaborative, and reflective activities.

This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.

Where it fits

MMA3001 is part of 3 areas of study in the 2026 handbook.

Contacts

Unit Coordinators
Dr Yeoh Chin Vern
Dr Callum Atkinson
Chief Examiners
Dr Callum Atkinson

Common questions

What are the prerequisites for MMA3001?

You need ENG2005 and (ENG1014 or ENG1060) before you enrol.

What can I take after MMA3001?

MMA3001 is a prerequisite or corequisite for 1 unit, including MMA3101.

When is MMA3001 offered?

In 2026, MMA3001 runs in Semester 2 at Clayton and Malaysia.

How much work is MMA3001?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does MMA3001 have an exam?

No. MMA3001 has 5 assessment tasks and no exam.

Which majors and minors include MMA3001?

MMA3001 is part of Aerospace engineering; Mechanical engineering; and Robotics and mechatronics engineering.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Engineering
Organisational unit
Department of Mechanical and Aerospace Engineering
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Available
Handbook years
20262027