The annual UNSW Data Science Work Experience week aims to inspire and engage Year 10 students across NSW with the importance and relevance of data science to everyday life and work. This presentation gives an overview of the datasets that we use during the Year 10 Work Experience.

"Random Forests" are used everywhere, and for good reason! Random Forest is a powerful and versatile machine learning algorithm that grows and combines multiple decision trees to create a "forest". It sounds very complex, but learning to use them is very intuitive, especially if you got a USNW codeRs workshop to help you. JR will give a beginner-friendly introduction to Random Forests applied to classification problems. Check workshop material at: https://unsw-coders.netlify.app/workshops/2021-07-30-randomforest/

Spatial data is essential for understanding many phenomena in natural and social sciences, and maps are used in a variety of fields to visualise data and results in an appealing and interpretive way. In this workshop I will show examples of how to work with geospatial data in R, including some basic geospatial analysis.

This is part of a series of introductory tutorials to work with geo-spatial data in R. For this tutorial we will import and read spatial objects using some libraries in R. We will explore three packages that allow us to read spatial data in vector and raster format, and give examples of operations, analysis and visualisation of such data.

Reproducible code makes your (research) life easier. Reproducible code helps you in case of emergency. Well documented code will make you famous (not really, but at least one step closer to fame...).

Summary of indicative maps of the distribution of ecosystem functional groups of the IUCN Global Ecosystem Typology

One slide description of my work at the Centre for Ecosystem Science, UNSW

Fire Ecology Traits for Plants: A database for fire research and management

Some tips on how to share your research data and code. UNSW CES Skills seminar / 20th April 2023 / JR Ferrer-Paris

Seminario virtual CEM - IUCN Tipología Global de Ecosistemas