Editing Community Data Science Course (Spring 2017) (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, and will teach basic tools and techniques for data analysis and visualization. In order to efficiently cover an end to end data analysis project, we will focus on publicly available data sets from the United States Government and the City of Seattle. Our goal is to enable you to gather and analyze data from any available source, but there are often subtle differences between data providers, and I would prefer that we see the full process once than get bogged down in data collection. Time will also be reserved to cover data access for popular social media platforms including Twitter.

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. We will focus on effectively answering questions about social media by writing your own software and by managing and communicating more effectively with programmers.


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 a publicly available data source.
* Read web API documentation and write Python software to parse and understand a new and unfamiliar 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 undeclared assumptions in their colleague's work.