UnitLevel 4Undergraduate

ENE4044 AI applications for civil and environmental engineers

Faculty of Engineering

ENE4044 AI applications for civil and environmental engineers is a level 4, 6-credit-point, undergraduate unit from the Faculty of Engineering, offered in 2026 in Semester 2 at Clayton. It needs ENG2005.

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

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

Reviews

No reviews yet

No reviews yet. Be the first to review ENE4044.

Requisites

Before ENE4044

Prerequisites

Pass these before you enrol.

Prohibitions

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

After ENE4044

No unit lists ENE4044 as a prerequisite in the 2026 handbook.

Equivalent units

The same content under another code. Only one of them counts.

Overview

This unit explores integrating artificial intelligence (AI) and machine learning (ML) technologies within engineering, including the civil and environmental sectors, focusing on their application for big data management and harnessing the power of industry-collected data. It will focus on leveraging cutting-edge technology to address current challenges, safeguard future sustainability, unravel potential risks, and develop intelligent systems to navigate the complexities of tomorrow's environmental landscape.

The unit aims to equip you with the necessary industry-applicable skills and knowledge to apply AI and ML in addressing critical issues within the civil and environmental business significantly enhancing your job-market readiness and employability in the era of AI. The blend of theoretical understanding, practical application, and ethical considerations ensures a comprehensive learning experience. You will apply your skills to real-world challenges and data brought to you by industry mentors who will guide you in exploring the entire process of delivering an industry-relevant project.

Offerings in 2026

Teaching periodCampusMode
Second semesterClaytonOn campus

Assessment

  • QuizzesQuiz / Test
    20%
  • AssignmentWritten
    40%
  • Group final project reportProject
    20%
  • Group oral presentationPresentation
    20%

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

    Define and justify the principles and methodologies of AI and ML for the civil and environmental sectors.

  2. 2

    Apply AI techniques and work with ML algorithms to manage big data and explore solutions for real-world problems in these sectors.

  3. 3

    Evaluate social biases, risks and ethical considerations associated with AI implementations.

  4. 4

    Conduct independent research on adoption barriers and present findings on AI applications in engineering businesses.

Workload and teaching

  • Workshops24 hours
  • Practical activities24 hours
  • Teaching approachActive 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.

Where it fits

ENE4044 is part of 4 areas of study in the 2026 handbook.

Contacts

Unit Coordinators
Dr Arash Zamyadi
Chief Examiners
Dr Arash Zamyadi

Common questions

What are the prerequisites for ENE4044?

You need ENG2005 before you enrol.

When is ENE4044 offered?

In 2026, ENE4044 runs in Semester 2 at Clayton.

How much work is ENE4044?

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

Does ENE4044 have an exam?

No. ENE4044 has 4 assessment tasks and no exam.

Which majors and minors include ENE4044?

ENE4044 is part of Civil engineering, Environmental engineering, Environmental engineering and Sustainable engineering.

More details

Credit points
6
Level
4
Study level
Undergraduate
Faculty
Faculty of Engineering
Organisational unit
Department of Civil and Environmental Engineering
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Available
Handbook years
202520262027