COMP 648
Machine Learning
Machine learning techniques to analyse and model land-use data.
Course overview
In this course, you'll build the core technical skills needed to succeed in the Master of Artificial Intelligence for Land Use programme and apply Machine Learning in land-based sectors.
Machine Learning is a game-changer for land-based industries. With Aotearoa New Zealand’s agri-sector thriving and Māori food and fibre assets growing rapidly, there’s a national push to develop AI talent. This course directly supports that goal by preparing you to fill skill gaps and lead data-driven innovation in agriculture, forestry, environmental management, and beyond.
You'll learn how to work with data, build predictive models, and explore real-world applications through case studies, including those focused on Māori land-use contexts. Whether you're aiming to innovate in agriculture, forestry, or environmental planning, this course sets you up with the tools to make a real impact.
This course is designed to help you:
- Master data preprocessing and feature selection techniques for Machine Learning
- Build clear, insightful data visualisations and use them to draw meaningful conclusions
- Develop, evaluate, and optimise predictive models using real-world datasets
Course information
| Available semesters | Semester 1 2026 |
|---|---|
| Credits | 40 |
| Domestic fees | $3,130.00 |
| Recommended Preparation | COMP 636 or equivalent |
What you will learn
After successfully completing this course, you will be able to:
- Perform data preprocessing and feature selection tasks for Machine Learning applications
- Create insightful and accurate data visualisations for land-use analysis
- Develop Machine Learning models using real-world datasets for predictive modelling
- Evaluate the performance of Machine Learning algorithms for forecasting outcomes
Course examiners
Thilini Bhagya
Lecturer
Centre for Geospatial and Computing Technologies
Thilini.Bhagya@lincoln.ac.nz