Editing Community Data Science Workshops (Spring 2015)
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:'''Location:''' Morning in [http://uw.edu/maps/?sav Savery Hall (SAV) 260]; Afternoon in [http://www.washington.edu/maps/#!/cmu Communications (CMU)] 104, 126 and 242 | :'''Location:''' Morning in [http://uw.edu/maps/?sav Savery Hall (SAV) 260]; Afternoon in [http://www.washington.edu/maps/#!/cmu Communications (CMU)] 104, 126 and 242 | ||
An important step in doing data science is collecting data. The goal of this session will be to teach participants how to get data from the [https://en.wikipedia.org/wiki/Application_programming_interface public application programming interfaces] ("APIs") common to many social media and online communities. Although we will use the APIs provided by Wikipedia, Twitter, and Socrata in the session, the principles and techniques are common to many other online communities. An outline for the lecture can be found [[Community_Data_Science_Workshops_(Spring_2015)/Day_2_Lecture|here]], and some info about the projects can be found [[Community_Data_Science_Workshops_(Spring_2015)/Day_2_Projects|here]]. | |||
An important step in doing data science is collecting data. The goal of this session will be to teach participants how to get data from the [https://en.wikipedia.org/wiki/Application_programming_interface public application programming interfaces] ("APIs") common to many social media and online communities. Although we will use the APIs provided by Wikipedia, Twitter, and Socrata in the session, the principles and techniques are common to many other online communities. | |||
=== Session 3: Data Analysis and Visualization (May 9) === | === Session 3: Data Analysis and Visualization (May 9) === | ||
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:'''Location:''' Morning in [http://uw.edu/maps/?sav Savery Hall (SAV) 260]; Afternoon in [http://www.washington.edu/maps/#!/cmu Communications (CMU)] 104, 126 and 242 | :'''Location:''' Morning in [http://uw.edu/maps/?sav Savery Hall (SAV) 260]; Afternoon in [http://www.washington.edu/maps/#!/cmu Communications (CMU)] 104, 126 and 242 | ||
The goal of data science is to use data to answer questions. In our final session, we will use the Python skills we learned in the first session and the datasets we've created in the second to ask and answer common questions about the activity and health of online communities. We will focus on learning how to generate visualizations, create summary statistics, and test hypotheses. The lecture outline can be found [[Community_Data_Science_Workshops_(Spring_2015)/Day_3_Lecture|here]], and the projects can be found [[Community_Data_Science_Workshops_(Spring_2015)/Day_3_Projects|here]]. | |||
The goal of data science is to use data to answer questions. In our final session, we will use the Python skills we learned in the first session and the datasets we've created in the second to ask and answer common questions about the activity and health of online communities. We will focus on learning how to generate visualizations, create summary statistics, and test hypotheses. | |||
== Resources == | == Resources == | ||
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* [[Community Data Science Workshops (Spring 2015)/Day 1 projects|Saturday April 11th projects]] | * [[Community Data Science Workshops (Spring 2015)/Day 1 projects|Saturday April 11th projects]] | ||
* [http://www.codecademy.com/courses/python-beginner-en-kSQwt Introduction to Python CodeAcademy exercises] | * [http://www.codecademy.com/courses/python-beginner-en-kSQwt Introduction to Python CodeAcademy exercises] | ||
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