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+++ b/README.md
@@ -1,62 +1,23 @@
-## Open-source Tools for Training Resources - OTTR
+## Tools for Reproducible Workflows
-Go to [ottrproject.org](https://www.ottrproject.org/) to get started! :tada:
-
-The purpose of this course template and guide is to make course publishing maintenance across multiple different platforms _less painful_.
-
-_This template and guide helps you_:
-
-- Edit and write a course in [RMarkdown files](https://rmarkdown.rstudio.com/) and have it published to multiple different platforms:
- - [Leanpub](https://leanpub.com/bookstore?type=course)
- - [Bookdown](https://bookdown.org/)
- - [Coursera](https://www.coursera.org/)
-- Have [Github action robots](https://www.ottrproject.org/customize-robots.html) do your repetitive tasks like spell check and re-rendering.
-- Use [automagic conversion](https://github.com/jhudsl/ottrpal) to ease the lift of prepping the material for different platforms' formats.
-- Use [our Docker image](https://hub.docker.com/repository/docker/jhudsl/base_ottr) for consistency across authors as well as to help you [avoid dependency hell](https://en.wikipedia.org/wiki/Dependency_hell).
-
-[See the OTTR pre-print here!](https://arxiv.org/abs/2203.07083)
-
-
-
-## Courses that have been made using this template:
-- [Documentation and Usability](https://jhudatascience.org/Documentation_and_Usability/)
-- [Leadership for Cancer Informatics Research](https://jhudatascience.org/Informatics_Research_Leadership/)
-- [Reproducibility in Cancer Informatics](https://jhudatascience.org/Reproducibility_in_Cancer_Informatics/)
-- [Advanced Reproducibility in Cancer Informatics](https://jhudatascience.org/Adv_Reproducibility_in_Cancer_Informatics/)
-
-## To Get Started
-- Go to the [ottrproject.org](https://www.ottrproject.org/).
-- Check out the [rendered version of the template](https://jhudatascience.org/OTTR_Template/).
-- Please take a look at the [code of conduct](./code_of_conduct.md).
-- If you encounter any problems or have ideas for improvements to this template repository or this getting started guide, please [file an issue here](https://github.com/jhudsl/OTTR_Template/issues/new/choose)! Your feedback is very much appreciated.
-
-
-
-# {Course Name}
-
-[](https://github.com/jhudsl/OTTR_Template/actions/workflows/render-all.yml)
-
-This course was created from [this GitHub template](https://github.com/jhudsl/OTTR_Template).
-
-You can see the rendered course material here: {Link to rendered bookdown and/or to the Leanpub.}
-
-If you would like to contribute to this course material, take a look at the [getting started GitHub wiki pages](https://github.com/jhudsl/OTTR_Template/wiki).
-
-## About this course
-
-This course introduces {info on what this course introduces}
+This is the GitHub repository for the Tools for Reproducible Workflows course. This course explores a variety of tools that can assist with reproducible data analysis from a broad range of fields. This course was funded as part of a series of courses in the [Training Module for Reproducible Data Science Research project](https://reporter.nih.gov/search/k_pXzn8wfUeEvaWpnzIToA/project-details/10663171).
## Learning Objectives
-This course will teach learners to:
+This course will demonstrate how to:
+
+1. Explain best practices for making analyses more reproducible and transparent
+2. Use special features in RStudio for efficiency and reproducibility
+3. Configure and organize projects for data analysis using the here package and the ProjectTemplate package
+4. Create reproducible reports using RMarkdown and Quarto
+5. Write custom functions for reuse of code
+6. Test functions with the testthat package
+7. Setup and use Git and GitHub to track changes over time 8. Share data and code publicly
-- {You can use https://www.bobpikegroup.com/trainer-blog/5-steps-to-writing-clear-and-measurable-learning-objectives to define some learning objectives here}
-- {More learning objectives}
-## Encountering problems?
+This course was built with [OTTR](https://www.ottrproject.org/)
-If you are encountering any problems with this course, please file a GitHub issue or contact us at {Some email or web address with a contact form}.

All materials in this course are licensed under a Creative Commons Attribution 4.0 International License unless noted otherwise.