Splitting data/README into courses-books.md

hiranp · Nov 3, 2019 · 9db4dbc · 9db4dbc
1 parent c3ee2c9
commit 9db4dbc
Show file tree

Hide file tree

Showing 2 changed files with 27 additions and 12 deletions.
diff --git a/data/README.md b/data/README.md
@@ -91,18 +91,9 @@ See [Visualisation](../README-details.md#visualisation-1)
 
 See under [Cheatsheets](../README-details.md#cheatsheets)
 
-## Course / books
-
-- [Data Science Primer](https://elitedatascience.com/primer)
-- [27 Amazing Data Science Books Every Data Scientist Should Read](https://www.analyticsvidhya.com/blog/2019/01/27-amazing-data-science-books-every-data-scientist-should-read/)
-- [Coursera course: Getting and Cleaning Data](https://www.coursera.org/learn/data-cleaning?recoOrder=20&utm_medium=email&utm_source=recommendations&utm_campaign=u0faoCsqEemEkbug8nMVQQ)
-- [Data Science courses on Coursera](https://www.coursera.org/learn/competitive-data-science)
-- [Data courses on Udemy](https://www.udemy.com/courses/search/?ref=home&src=ukw&q=data)
-- [Data courses on Udacity](https://eu.udacity.com/courses/school-of-data-science)
-- [Latest Machine learning, visualization, data mining techniques. Online Masters in Data Analytic from Penn State](https://twitter.com/analyticbridge/status/1102667686302179336)
-- [Data Science Handbook](https://github.com/RishiSankineni/Data-Science-Swag/blob/master/The%20Data%20Science%20Handbook.pdf)
-- [Coursera Course: Probability and distribution](
-https://media.licdn.com/dms/document/C511FAQGFKgIKuW_EEA/feedshare-document-pdf-analyzed/0?e=1571785200&v=beta&t=XyEEqUgi3y4L1hiZ7CxlxbAXyZmM_zcCCdn-Lr04ns8)
+## Courses / books
+
+See [Courses / books](./courses-books.md)
 
 ## Best practices / rules / an unordered list of high level or low level guidelines
 

diff --git a/data/courses-books.md b/data/courses-books.md
@@ -0,0 +1,24 @@
+# Courses / books
+
+- [Data Science Primer](https://elitedatascience.com/primer)
+- [27 Amazing Data Science Books Every Data Scientist Should Read](https://www.analyticsvidhya.com/blog/2019/01/27-amazing-data-science-books-every-data-scientist-should-read/)
+- [Coursera course: Getting and Cleaning Data](https://www.coursera.org/learn/data-cleaning?recoOrder=20&utm_medium=email&utm_source=recommendations&utm_campaign=u0faoCsqEemEkbug8nMVQQ)
+- [Data Science courses on Coursera](https://www.coursera.org/learn/competitive-data-science)
+- [Data courses on Udemy](https://www.udemy.com/courses/search/?ref=home&src=ukw&q=data)
+- [Data courses on Udacity](https://eu.udacity.com/courses/school-of-data-science)
+- [Latest Machine learning, visualization, data mining techniques. Online Masters in Data Analytic from Penn State](https://twitter.com/analyticbridge/status/1102667686302179336)
+- [Data Science Handbook](https://github.com/RishiSankineni/Data-Science-Swag/blob/master/The%20Data%20Science%20Handbook.pdf)
+- [Coursera Course: Probability and distribution](
+https://media.licdn.com/dms/document/C511FAQGFKgIKuW_EEA/feedshare-document-pdf-analyzed/0?e=1571785200&v=beta&t=XyEEqUgi3y4L1hiZ7CxlxbAXyZmM_zcCCdn-Lr04ns8)
+
+
+# Contributing
+
+Contributions are very welcome, please share back with the wider community (and get credited for it)!
+
+Please have a look at the [CONTRIBUTING](../CONTRIBUTING.md) guidelines, also have a read about our [licensing](../LICENSE.md) policy.
+
+---
+
+Back to [Data page (table of contents)](README.md)</br>
+Back to [main page (table of contents)](../README.md)