During the year we offer a series of workshop-style bootcamps to offer students a chance to learn new data skills just in time for the Data Dive and to continue to build students’ skills throughout the year.
Our bootcamps are open to anyone, so please feel free to join us and learn! This is also a great opportunity to talk to the organizers if you have any questions about Data Dive itself.
Please feel free to reach out with questions or suggestions for bootcamp topics at firstname.lastname@example.org.
Want to know what we’ve done in the past? Check out our previous bootcamps HERE.
Fall 2017 Bootcamps and Data Talks
Why do we data? Data 101 with Lynette Hoelter from ICPSR
Friday, October 27, 11:30-1:00pm in NQ 1255.
Speaker: Lynette Hoelter, Director of Instructional Resources and Development, ISCPR
In this session, we invite Lynette to speak to how organizations use data to drive social change, and how to find data sources to answer the questions you might ask at the Data Dive and beyond! The lead organizers of the event, Deepak and Srishti, will be following up with a short technical overview of some data science frameworks that people use in the process of deriving information from data and communicating findings to community partners. We will finish up with an all-you-ever-wanted-to-know question answer session on what you need to know and do on the day of the Dive, volunteer opportunities and how you can contribute to the Data Dive this year!
You can find the slides from Lynette’s talk here.
You can find the slides from Deepak’s talk here.
Data Manipulation with Python
Saturday, November 11, 8:30-9:30 am in NQ 1255
Hosted by: Jeff Lockhart, Institute of Social Research
In this session, we will explore a “cookbook” of “recipes” for common data manipulation and wrangling tasks, specifically geared toward manipulating your client’s raw data during the data dive. We will specifically focus on using Anaconda and a variety of common Python packages to execute recipes for merging datasets, breaking and rearranging data fields, analyzing data, summarizing by groups, handling categorical data, creating indicator variables, and scaling quantitative variables, among other exciting things! If we have time, we will also look at some quick, useful data vis tools in Python.
Data Visualization with Tableau
Saturday, November 11, 12-1pm in NQ 1255
Hosted by: TBD
In this session, we’ll cover the process of loading, analyzing, and visualizing data in Tableau, introducing the Tableau