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ESS 523A - Environmental Data Science Data Applications: Introduction

  • 5 credits
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Explore tools and best practices for working with large environmental datasets primarily using the programming language R. Cover technical topics like: data types, file management, iteration, functional programming, debugging, code management and collaboration with git and GitHub. Use these tools to analyze environmental data using statistical approaches like: linear models, trend analysis, simple machine learning techniques.


STAT 158 (Introduction to R Programming or STAT 301)