Editing Community Data Science Course (Spring 2016) (section)

== Overview and Learning Objectives ==
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In a world that is increasingly driven by software and data, developing a basic level of fluency with programming and the basic tools of data analysis is a crucial skill. This course will introduce basic programming and data science tools to give students the skills to use data to answer questions about social media and online communities.

In particular, the class will cover the basics of the Python programming language, an introduction to web APIs including APIs from Wikipedia and Twitter, and will teach basic tools and techniques for data analysis and visualization. As part of the class, participants will learn to write software in Python to collect data from web APIs and process that data to produce numbers, hypothesis tests, tables, and graphical visualizations that answer real questions. The class will be built around student-designed independent projects. Every student will pick a question or issue they are interested in pursuing in the first week and will work with the instructor to build from that question toward a completed analysis of data that the student has collected using software they have written.

This is not a computer science class and I am not going to be training you to become professional programmers. This introduction to programming is intentionally quick and dirty and is focused on what you need to get things done. If you want to become a professional programmers, this is probably not the right class. If you want to learn about programming so that you can more effectively answer questions about social media by writing your own software and by managing and communicating more effectively with programmers, you are in the right place.

I will consider this class a complete success if, at the end, every student can:

* Write or modify a program to collect a dataset from the Wikipedia and Twitter APIs.
* Read web API documentation and write Python software to parse and understand a new and unfamiliar JSON-based web API.
* Use both Python-based tools like MatPlotLib as well as tools like LibreOffice, Google Docs, or Microsoft Excel to effectively graph and analyze data.
* Use web-based data to effective answer a substantively interesting question and to present this data effectively in the context of both a formal presentation and a written report.
* The ideal outcome is that students will have the working knowledge to more effectively collaborate with data professionals in their careers. They will be both more informed about the process and more likely to spot un-declared assumptions in their colleague's work.