Differences

This shows you the differences between two versions of the page.

--- notes:python [2017/03/15 00:54] – hkimscil
+++ notes:python [2017/09/08 08:00] (current) – hkimscil
@@ Line 1: / Line 1: @@
+https://www.coursera.org/specializations/data-science-python#courses
 [[https://www.coursera.org/learn/python-data-analysis/supplement/68grE/syllabus|Syllabus: Applied Data Science with Python]]
   - basic recommendation [[https://www.coursera.org/learn/python|Programming for Everybody]]
@@ Line 14: / Line 16: @@
     - law and business degrees.
-And here they apply data driven methodologies to aid in their discovery, from statistical analysis, machine learning and text mining, to information visualization. And this need for data driven intelligence and skills is growing in companies and organizations throughout the world. Let's start with a look at the roots of the field of data science.
+And here they apply data driven methodologies to aid in their discovery, from
+  * statistical analysis,
+  * machine learning and
+  * text mining,
+  * information visualization.
+  - Data Exploration and Preparation,
+  - Data Representation and Transformation
+  - Computing with Data with R and Python
+  - Data Modeling
+  - Data Visualization and Presentation
+http://www.data-analysis-in-python.org/index.html
+https://programminghistorian.org/lessons/
+https://nealcaren.github.io/python-tutorials/
+https://lingfeiwu1.gitbooks.io/data-mining-in-social-science/content/python_for_data_analysis/