Working Groups
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Short Courses and Workshops
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Mailing ListsFor communication beyond this webpage, we have two internal mailing lists. UW users are welcome to subscribe themselves at the following links:
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Person and Affiliation: |
Location: |
Availability: |
Expertise: |
University of Wyoming |
Agriculture Building C - Room 316 & 323 |
General computing with R, statistics and spatial analyses (R, ArcGIS, and other open source software). |
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University of Wyoming |
Amplicon sequence processing, general computing in R, general stats with a microbial ecology focus, basic shell scripts. |
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University of Wyoming - Stats Dept. |
Ross Hall - Room 333 |
Monday: 2:30pm - 4:00pm Tuesday: 1:00pm - 4:00pm |
Statistical consulting, R: statistical analyses, data wrangling, data visualization, JAGS. |
WEST, Inc. |
E-Meeting |
Deep learning (computer vision and Artificial Neural Nets); Bayesian modeling; Ecological and epidemiological modeling and simulations; Python, R, Stan. |
WEST (an environmental and statistical consulting company founded in Wyoming) hosts paid data-science internships in partnership with Wyoming EPSCoR. These are suitable for undergraduate students, graduate students, and recent alumni. See this page for more information.
We have considered hosting a local data science competition at UW. We would use this as an opportunity to learn form one another, with in person meetings and discussions of the projects and entries, including by judges and attendees who are data science professionals. Additionally, some students are interested in Kaggle and other competitions. More information in on the Data Science Competitions page.
UW courses related to data science [LINK]
Materials from Fall 2017 'R Club' meetings
Online courses related to data science
How do we share code and Rmarkdown output?
Consider shared projects on Rstudio.cloud
How to use git
How to get access to cluster computing resources at UW
How to ssh to the cluster computer (Teton, teton.uwyo.edu ???)
How to submit jobs to the shared queue for the cluster computing with SLURM
Example codes for JAGS models and their use from R, with rjags
NeuralNet for Titanic survivorship data