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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., 28-Mar-17
E.g., 28-Mar-17
October 31, 2016
Coordinator:
Chris Hench

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.

October 31, 2016
Coordinator:
Erin LeDell

The focus of this workshop is machine learning using the h2o and h2oEnsemble R packages. H2O is an open source distributed machine learning platform designed for big data, with the added benefit that it is easy to use on a laptop (in addition to a multi-node Hadoop or Spark cluster).

October 28, 2016
Coordinator:
Shelly Steward

In this workshop, we will explore the process of moving from coded data to conclusions, the logics of analysis, identifying relationships in data, and building arguments with qualitative data.

October 28, 2016
Coordinator:
Susan Powell

This workshop will introduce the ArcGIS Online (AGOL) platform. AGOL is a web-based mapping software that allows you to build maps and explore data online. Topics to be covered include how to construct a simple web map from a spreadsheet of data, perform basic spatial analysis and queries, and publish the map to the web.

October 27, 2016

Join the Qualtiative Methods Group for a conversation with Dr. Erin Kerrison about using mixed-methods to collect data about hard-to-reach populations.

October 26, 2016
Coordinator:
George Ng

Come hear George Ng, Cyence Co-Founder & Chief Technology Officer, speak about practical quantitative data applications, and transitioning to industry and start-ups.

October 26, 2016
Coordinator:
Natalie Ahn

Are you trying to search for or clean up certain segments of text in your documents or data files, but it's taking hours to search and replace, because you have to type many slightly different versions of the keywords you're searching for?

October 26, 2016
Coordinator:
Isabelle Cohen

This three-part series will cover the following materials:

Part I: Introduction (Wednesday, October 12)

October 25, 2016
Coordinator:
Evan Muzzall

The R for Data Science workshop series is a four-part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.

Part 3: Analyzing Data

October 25, 2016
Coordinator:
Tarunima Prabhakar

This three-part series will focus on how to maximize functions in Microsoft Excel, set up database-like structures, and build various kinds of reports. By the end of this series, participants will be able to import text data, perform basic mathematical operations and character-based functions, sort and filter data, and utilize pivot tables.

October 24, 2016
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 3 Topics:

October 21, 2016
Coordinator:
Patty Frontiera

This introductory workshop is geared towards social scientists and digital humanitists who have data - spreadsheets, scanned maps, digital photos, etc -  that they want to display on a map. We explore these tasks in CARTO, a versatile web mapping and geospatial analysis tool.

October 21, 2016
Coordinator:
Juan Shishido

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python.

In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

We plan to cover:

October 20, 2016

The Research in Progress Working Group is proud to present a panel of PhD candidates and students from diverse disciplines who will discuss the challenges and opportunities of conducting field experiments in the global south.

October 20, 2016

Join the Qualitative Methods Group for a conversation with Dr. Cybelle Fox about analyzing archival documents.

October 20, 2016 to November 3, 2016
Coordinator:
Scott McGinnis

XML is a standard from which many encoding languages are created, and it structures much of the data on the Internet.

October 19, 2016
Coordinator:
Isabelle Cohen, Saika Belal

This three-part series will cover the following materials:

Part I: Introduction (Wednesday, October 12)

October 19, 2016
Coordinator:
Alex Estes

Students will learn the basics of cleaning, transforming, and formatting text data. They will pull specific elements out of text strings, and pull simple metrics from text data, such as word counts, syntax quantification via part of speech (POS) tagging, and sentiment polarity. Students will be introduced to topic modeling and word2vec methods.

October 18, 2016

The Literature and Digital Humanities Working Group would like to present the following talk as a follow up to 'Editions Inside of Archives: Literary Editing and Preservation at the Mark Twain Project' (Christopher Ohge).

October 18, 2016
Coordinator:
Shinhye Choi

The R for Data Science workshop series is a four-part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.

Part 2: Clean and Tidy Data

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