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This is an archive of our past training offerings. We are looking to include workshops on topics not yet covered here. Is there something not currently on the list? Send us a proposal.

E.g., 26-Jul-17
E.g., 26-Jul-17
March 14, 2017
Coordinator:
Evan Muzzall

It is often said that 80% of data analysis is spent on the process of cleaning and preparing the data. This workshop will introduce tools (notably dplyr and tidyr) that makes data wrangling and manipulation much easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful stuff.

March 13, 2017
Coordinator:
Alex Estes

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 3 Topics:

March 13, 2017
Coordinator:
Andrew Seier

This workshop will introduce the plotly Python module and guide attendees from the getting-started phase through the creation of complex, beautiful visualizations that may be shared on the web.

March 13, 2017
Coordinator:
Ben Gebre-Medhin

This non-technical workshop provides an overview of computational text analysis methods and tools. No experience in this area is expected or required. The goal is to provide an orientation for those wishing to go further with text analysis and interpret results of these methods.

March 10, 2017
Coordinator:
Chris Hench

Git is a powerful tool for keeping track of changes you make to the files in a project. You can use it to synchronize your work across computers, collaborate with others, and even deploy applications to the cloud. In this workshop, we'll learn the basics of understanding and using Git, including working with the popular "social coding" website, GitHub.

March 10, 2017
Coordinator:
Chris Kennedy

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data.

March 9, 2017
Coordinator:
Michael Sholinbeck

Participants in this workshop will learn about some of the issues surrounding the collection of health statistics, and will also learn about authoritative sources of health statistics and data. We will look at tools that let you create custom tables of vital statistics (birth, death, etc.), disease statistics, health behavior statistics, and more. The focus will be on U.S.

March 8, 2017

Join us for a presentation by Eduardo Escobar!

March 8, 2017
Coordinator:
Isabelle Cohen

This three-part series will cover the following materials:

Part 1:  Introduction (Wednesday, March 1)

March 7, 2017
Coordinator:
Drew Hart, Chris Muller

This two-hour course will review the fundamental concepts of GIS, demonstrating them through basic mapping and analysis of a variety of spatial datasets.

March 7, 2017
Coordinator:
Evan Muzzall

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!

Workshop: Weighting Data
March 7, 2017
Coordinator:
Thomas L. Piazza

This workshop will cover the main types of weighting, to correct for bias in sample data.

March 6, 2017
Coordinator:
Natalie Ahn

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 2 Topics:

March 6, 2017
Coordinator:
Evan Muzzall

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data.

March 3, 2017
Coordinator:
Isabelle Cohen

This workshop will introduce participants to the basics of data and do-file organization to make working in Stata easier. By the end of the workshop, participants will have an understanding of the importance of data organization, and have seen examples of potential structures for how to organize data files, do files, and other documentation.

March 3, 2017
Coordinator:
Patty Frontiera

This workshop provides an introduction to working with and visualizing spatial data in R. We give an overview of spatial data types and methods for importing and creating spatial data.  Participants will learn the basic tools for plotting data on a map and customizing the symbology.  We will also introduce methods for defining and transforming coordinate reference systems.

March 2, 2017

**********Please note: This event has been canceled.**********

Come enjoy refreshments and informal networking with other qualitative scholars. Drop in whenever you'd like!

March 2, 2017
Coordinator:
Deepa Kalpathi

Tableau is a data analysis software suite that creates data driven visualizations without programming. The software works with a variety of input data sources and format sources. Tableau output graphics can be combined together to create interactive dashboards that can be easily shared online. Come learn how to get started with this powerful, widely used visualization tool! 

March 1, 2017
Coordinator:
Saket Saurabh

This hands-on workshop will demonstrate ways to automate data operations--connect, manage, monitor, and transform data quickly--so you can increase analytical productivity and focus on machine learning.

Prior knowledge: Familiarity using and manipulating large data sets for machine learning or advanced analytics.

March 1, 2017
Coordinator:
Saika Belal

This three-part series will cover the following materials:

Part 1:  Introduction (Wednesday, March 1)

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