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    An Introduction to the R Programming Environment
    An online module introducing students and biologists to R, published in American Phytopathological Society
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    Introduction to Earth Data Science Textbook
    Introduction to Earth Data Science is an online textbook for anyone new to open reproducible science and the Python programming language. There are no prerequisites for this material, and no prior...
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    Earth Analytics in R Course
    Earth analytics is an advanced, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
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    Earth Analytics Bootcamp Course
    The Earth Analytics Bootcamp is a three-week introductory-level course taught by instructors in Earth Lab and is a part of the Professional Certificate in Earth Data Analytics - Foundations at CU...
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    DCS 105 Calling Bull F24 Schedule
    Schedule overview for Bates College Course DCS 105 Calling Bull
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    Writing Clean Code in R Workshop
    When working with data, you often spend the most amount of time cleaning your data. Learn how to write more efficient code using the tidyverse in R.
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    Introduction to Version Control and Git Workshop
    Learn how to use version control with Git to work collaboratively and back up your work.
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    REMNet Tutorial, R Part 5: Normalizing Microbiome Data in R 5.2.19
    Video on normalizing microbiome data from the Research Experiences in Microbiomes Network
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    Introduction to Python for Data Science Course
    Free Introduction to Python for Data Science Course at DataCamp
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    Introduction to R Course
    Free Introduction to R Course at DataCamp
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    Pennies to The Moon Data Byte Series
    This series of Rbyte activities explores the concept of debunking using Fermi Estimation, R, and ChatGPT.
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    Responses to Climate Change in California Chipmunks: Move, Adapt, or Die
    A series of three modules using data from natural history museum collections to examine responses to climate change in multiple chipmunk species. Elevation and morphological data, beginner skills...
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    Genome Sequence Data in R using Biostrings (Swirl Lesson)
    By the end of this lesson, students should be able to load FASTA files into R as DNAStringSets and use width() and alphabetFrequency(), combined with other functions like sum() and mean(), to...
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    Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching
    This lesson plan was created to teach RNAseq analysis as a part of GCAT-SEEK network. It is provided here, both in finished form and with the modifiable source code, to allow flexible adaptation to...
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    Curvature and Maximum Permissible Speeds
    In this activity students will compute the curvature of a section of commuter rail and use it to determine a safe speed at which a train should can round the corner without tipping or derailing....
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    Biodiversity Conservation in Agriculture
    Biodiversity is decreasing rapidly each year and agriculture is a large contributor. In order to minimize biodiversity loss, we must study how local and landscape management in agriculture impact...
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    Earth Analytics in Python Course
    Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
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    Get Started With GIS in Open Source Python Workshop
    There are a suite of powerful open source python libraries that can be used to work with spatial data. Learn how to use geopandas, rasterio and matplotlib to plot and manipulate spatial data in...
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    Hardy-Weinberg Equilibrium: a swirl resource
    Students will use swirl to understand Hardy-Weinberg equilibrium. The lesson starts with observed numbers of individuals for each genotype, and students will work through a number of steps to...
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    Analyzing Nutrient Simulation Experiments with a one-way ANOVA
    We discuss what tests are appropriate to analyze the data from nutrient simulation experiments. They will conduct one-way ANOVAs and a post hoc test using a dummy dataset and interpret the results.
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