ENERGY 797 · also ENVIRON 797
Time Series Analysis for Energy and Environment Applications
Luana Lima
Description from DukeHub
This course focuses on time series analysis, modeling, and forecasting, specifically within the context of energy and the environment. Lectures will include theory and applications using R programming language. Datasets from organizations like US Energy Information Administration (EIA), National Oceanic and Atmospheric Administration (NOAA), National Renewable Energy Laboratory (NREL) and US Geological Survey (USGS) will be used. Upon completion of the course, students will be able to use R to carry out basic statistical modeling and analysis as well as fitting models to data. The primary objective of the course is to empower students to extract meaningful predictions and insights from data.
Skills
- data and statisticsdescription: "time series" and 5 more
- programmingAI review: "use R to carry out basic statistical modeling"
AI-resilient: 1 of 5
- Yes: Physical, lab or field work · "laboratory"
- No: Live work with people
- No: Judgment someone is accountable for
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
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