Community Data Science Workshops (Spring 2015)

Registration Closed Unfortunately, registration is now closed. If you have experience to share, it's not too late to sign up as a mentor by joining the mentor list.

More photos from past workshops.

The Community Data Science Workshops in Spring 2015 are a series of project-based workshops being held at the University of Washington for anyone interested in learning how to use programming and data science tools to ask and answer questions about online communities like Wikipedia, Twitter, free and open source software, and civic media.

The workshops are for people with absolutely no previous programming experience and they bring together researchers and academics with participants and leaders in online communities. The workshops are run entirely by volunteers and are entirely free of charge for participants, generously sponsored by the UW Department of Communication and the eScience Institute. Participants from outside UW are encouraged to apply.

Our goal is that, after the three workshops, participants will be able to use data to produce numbers, hypothesis tests, tables, and graphical visualizations to answer questions like:

• Are new contributors in Wikipedia this year sticking around longer or contributing more than people who joined last year?
• Who are the most active or influential users of a particular Twitter hashtag?
• Are people who join through a Wikipedia outreach event staying involved? How do they compare to people who decide to join the project outside of the event?

An earlier version of the workshops was run in Spring and Fall 2015 and the curriculum we used for both are online.

Registration

Unfortunately, registration is over and we were oversubscribed and we have a large waitlist. Sorry about that! This is our third set of workshops and we do hope to run more of these again in the future.

Interested in being a mentor? We are still interested in mentors, however. If you already have experience with Python, please consider helping out at the sessions as a mentor. Being a mentor will involve working with participants and talking them through the challenges they encounter in programming. No special preparation is required. And we’ll feed you! Because we want to keep a very high mentor to student ratio, recruiting more mentors means we can accept more participants. If you’re interested, sign up on our mentor mailing list or email makohill@uw.edu. Also, thank you, thank you, thank you!

Schedule

There will be a mandatory evening setup session 6:00-9:00pm on Friday April 10 and three workshops held from 9am-4pm on three Saturdays (April 11 and 25 and May 9). Each Saturday session will involve a period for lecture and technical demonstrations in the morning. This will be followed by a lunch graciously provided by the eScience Institute at UW. The rest of the day will be followed by group work on programming and data science projects supported by more experienced mentors.

Session 0: Setup and Programming Tutorial (April 10 evening)

Time: 6:00-9:00PM

Location: Communications (CMU) 104

Note: Because we expect to hit the ground running on our first full day, we will meet to help participants get software installed and to work through a self-guided tutorial that will help ensure that everyone has the skills and vocabulary to start programming and learning when we meet the following morning.

Come to Communications (CMU) 104 between 6:00 and 9:00pm. It's OK if you come a little late but you'll want to have as much time as you can to finish the setup and self-directed assignments so come as close to 6:30pm as you can. Most people will finish early but some people will definitely need the full 3 hours. It's hard to know in advance where problems will crop up so please come on time even if you are confident.

During this session, mentors will help you:

• set up your development environment
• learn how to execute Python code from a file and interactively from a Python prompt
• learn about printing and using Python as a calculator

Session 1: Introduction to Programming (and April 11)

Time: 9:45-4pm

Location: Morning in Savery Hall (SAV) 260; Afternoon in Communications (CMU) 104, 126 and 242

Come to Savery Hall (SAV) 260 by 9:45am (Note: it's not in the communication building). You will need time to get settled and setup. We will start lecturing promptly at 10am. There will be coffee!

• Morning, 10am-12:20 (SAV 260): A 2 hour lecture-based introduction to the Python programming language
• Lunch, 12:20-1pm (pizza in Room 126): We'll provide lunch
• Afternoon, 1pm-3:30pm (Room 104, 126, 242): Python practice through short projects on a variety of fun and practical topics
• Wrap-up, 3:30pm-4pm: Wrap-up, next steps, and upcoming opportunities for learning and practicing Python

Programming is an essential tool for data science and is useful for solving many other problems. The goal of this session will be to introduce programming in the Python programming language. Each participant will leave having solved a real problem and will have built their first real programming project.

Session 2: Importing Data from web APIs (April 25)

Time: 9:45-4pm

Location: Morning in Savery Hall (SAV) 260; Afternoon in 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 public application programming interfaces ("APIs") common to many social media and online communities. Although we will use the APIs provided by Wikipedia and Twitter in the session, the principles and techniques are common to many other online communities. An outline for the lecture can be found here, and some info about the projects can be found here.

Session 3: Data Analysis and Visualization (May 9)

Time: 9:45-4pm

Location: Morning in Savery Hall (SAV) 260; Afternoon in 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 here, and the projects can be found here.

Resources

The following materials are currently being updated by the mentors:

• Friday April 10th setup and tutorial
• Saturday April 11th lecture
• Saturday April 11th projects
• Introduction to Python CodeAcademy exercises
• Saturday April 25th lecture
• Saturday April 25th projects
• Introduction to APIs in Python CodeAcademy exercises - Includes information on using APIs from NPR, Bitly, Sunlight Foundation, and PlaceKitten
• Saturday May 9th lecture
• Saturday May 9th projects

About the Organizers

The workshops are being coordinated, organized by Benjamin Mako Hill, Jonathan Morgan, Tommy Guy, Ben Lewis, Dharma Dailey, Sage Ross, and a long list of other volunteer mentors. The workshops have been designed with lots of help and inspiration from Shauna Gordon-McKeon and Asheesh Laroia of OpenHatch and lots of inspiration from the Boston Python Workshop.

These workshops are an all-volunteer effort. Fundamentally, we're doing this because we're programmers and data scientists who work in online communities and we really believe that the skills you'll learn in these sessions are important and empowering tools.

The workshops are being supported by the UW Department of Communication and the eScience Institute.

If you have any questions or concerns, please contact Benjamin Mako Hill at makohill@uw.edu.