Training objectives
Section outline
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- Understand Fundamental Concepts: Define and distinguish between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning, including various learning paradigms such as
supervised, unsupervised, and reinforcement learning. - Apply AI in Environmental Contexts: Utilize AI tools and techniques for environmental applications, including biodiversity monitoring, climate modelling, remote sensing, and big data analysis related to air, water, and soil quality.
- Evaluate Ethical Implications: Assess the ethical considerations of deploying AI in environmental contexts, focusing on privacy, data sovereignty, automation impacts, and equitable decisionmaking.
- Understand Fundamental Concepts: Define and distinguish between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning, including various learning paradigms such as