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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
November 28, 2016
Coordinator:
Nancy Thomas

This workshop has been designed to introduce GIS to participants with little to no experience. Quantum GIS (QGIS), an open source geospatial desktop application, has been developing at a rapid pace, and has recently reached version 1.8. Its ease of use and accessibility (available for PC, Mac, and Linux platforms) has created a strong and active user community.

November 28, 2016
Coordinator:
Zawadi Rucks-Ahidiana

This workshop covers how to organize and analyze qualitative data in MaxQDA. The training will outline the key decisions researchers must make about approaching coding and what data is most relevant, as well as review how to set up a database, and use folders, codes, document variables, and queries in MaxQDA.

November 21, 2016
Coordinator:
Josh Pepper

PLEAE NOTE: This workshop was originally scheduled for Monday, 11/14 at 2:30-4:00pm. If you were registered for the 11/14 workshop, your status will carry over to this rescheduled date/time.

Come learn how to turn your data into powerful webmaps in R, by combing the power of Leaflet and Shiny!

November 17, 2016
Coordinator:
Saika Belal

This three-part series will cover the following materials:

Part I:  Introduction (Thurday, November 3)

November 17, 2016
Coordinator:
Akos Kokai

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:

November 16, 2016
Coordinator:
Natalie Ahn

This workshop addresses various topics in Natural Language Processing, primarily through the use of NLTK. We'll work with a corpus of documents and learn how to identify different types of linguistic structure in the text, which can help in classifying the documents or extracting useful information from them.

November 15, 2016
Coordinator:
Robin Einhorn, Patty Frontiera

This workshop will begin with a talk by UC Berkeley History Prof. Robin Einhorn on her research of taxation in the US. She will discuss how mapping these data is useful for revealing historical trends yet presents a technical challenge when dealing with 100 years worth of information. The second half of the talk will be a tutorial on mapping time series data in R.

November 15, 2016
Coordinator:
Thomas L. Piazza

This workshop is the first part of a two-part series on survey sampling. This first workshop will cover the basic principles and methods of sampling. Topics will include a discussion of the various types of samples, the creation of sampling frames, the use of stratification, and basic methods of selecting samples. Determining an appropriate sample size will also be discussed. 

November 14, 2016
Coordinator:
Josh Pepper

UPDATE: This workshop has been rescheduled for Monday, 11/21 at 2:30-4:00pm in Barrows 356 (D-Lab Convening Room). Please mark the change in your calendar.

Come learn how to turn your data into powerful webmaps in R, by combing the power of Leaflet and Shiny!

November 10, 2016
Coordinator:
Isabelle Cohen

This three-part series will cover the following materials:

Part I:  Introduction (Thurday, November 3)

November 9, 2016

In this process-oriented talk, Dr. Sacks will walk us through the ethical, logistical, conceptual, and methodological challenges related to investigating the impact of historical trauma and contemporary trauma on experiences of one research participant connected to the Tuskegee Syphilis Study. Dr.

November 8, 2016
Coordinator:
Susan Powell

Sometimes you just want/need to make a map! This workshop will provide a basic overview of the data sources, steps, and considerations necessary to transform an idea or a table of data to a publication-ready map.

No prior knowledge required.

November 7, 2016
Coordinator:
Josh Pepper

Come learn how to turn your data into beautiful maps using R!

November 4, 2016
Coordinator:
Erin LeDell

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

November 4, 2016
Coordinator:
Shinhye Choi

Please note: This workshop is hosted by the Geospatial Innovation Facility. Register here!

November 4, 2016
Coordinator:
Harrison Dekker

Tableau is a data analysis software suite that allows you to create data driven visualizations without programming. The software works with a wide variety of input data sources and formatssources. Your Tableau output graphics can be combined together to create interactive dashboards that you can share online.

November 3, 2016
Coordinator:
Saika Belal

This three-part series will cover the following materials:

Part I:  Introduction (Thurday, November 3)

November 2, 2016 to November 9, 2016
Coordinator:
Akos Kokai

Please note: This is a two-part workshop series. The first session will occur Wednesday, November 2 from 12:00pm to 3:00pm. The second session will occur Wednesdsay, November 9 from 12:00pm to 3:00pm. If you are registered for the November 2 session, your registration is valid for both days.

November 1, 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 4: Functions and Packages

November 1, 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.

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