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--- notes:python [2017/03/15 09:14] – hkimscil
+++ notes:python [2017/09/08 16:30] (current) – hkimscil
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+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 5: / Line 7: @@
   - Advanced Querying and data manipulation using //pandas//
   - Statistical Analysis with //nuimpy// and //scipy//
+  * programmers,
+  * behavioral scientists and
+  * data scientists
+    - computer science and information degrees,
+    - psychology degrees,
+    - law and business degrees.
+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/