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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., 23-Jun-18
E.g., 23-Jun-18
May 9, 2018
Coordinator:
Kimberly Rubens

This class will cover the basics of Excel, from simple formulas (SUM, COUNTIF) to more complex Excel features like Macros and the Data Analysis ToolPak.

May 7, 2018
Coordinator:
Kimberly Rubens

This class will cover the basics of Excel, from simple formulas (SUM, COUNTIF) to more complex Excel features like Macros and the Data Analysis ToolPak.

May 4, 2018
Coordinator:
Soumya Gupta

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.

May 4, 2018
Coordinator:
Geoff Bacon

In this workshop we will cover two main supervised text analysis methods, the dictionary method, and supervised classification. We will use list comprehension to implement the dictionary method, using sentiment analysis as our example.

May 4, 2018
Coordinator:
Evan Muzzall

R FUN!damentals Part 4: For-loops and Functions

Students will learn how to write for-loops and functions in R. You will learn how to personalize functions via control structures such as ‘if’ and ‘else’. These learning objectives will be exemplified through introduction to the construction and graphical representation of Monte Carlo resampling simulation.

May 3, 2018
Coordinator:
Lindsay Bayham

This interactive workshop will discuss how to analyze qualitative data, including how to develop codes, look for patterns, answer research questions, and build an argument in order to write the findings, discussion, and conclusion sections of a research paper. Researchers at any stage in the process are welcome.

 

May 3, 2018
Coordinator:
Soumya Gupta

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:

May 3, 2018
Coordinator:
Lindsay Bayham

This workshop focuses on how to organize and code qualitative data in Dedoose. The training will outline key decisions researchers must make in the coding process, as well as review how to start a new project and engage in basic tasks.

May 3, 2018
Coordinator:
Geoff Bacon

This hands on workshop builds on part 2 by introducing the basics of Python's scikit-learn package to implement unsupervised text analysis methods. This workshop will cover a) vectorization and Document Term Matrices, b) weighting (tf-idf), and c) uncovering patterns using topic modeling.

May 3, 2018
Coordinator:
Patty Frontiera

Come learn how to turn your data into beautiful webmaps using R and Leaflet, one of the most popular libraries for creating web maps. We’ll cover how to build the entire workflow from raw data to interactive map all within R, so your analysis and mapping are entirely reproducible.

May 3, 2018
Coordinator:
Evan Muzzall

R FUN!damentals Part 3: Data Exploration and Analysis

Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.

May 2, 2018
Coordinator:
Drew Hart

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:

May 2, 2018
Coordinator:
Josué Meléndez Rodríguez

This workshop focuses on how to organize and code qualitative data in MaxQDA. The training will outline key decisions researchers must make in the coding process, as well as review how to start a new project and engage in basic tasks. 

May 2, 2018
Coordinator:
Geoff Bacon

This hands on workshop goes through the common “preprocessing recipe” that is used as the foundation for a variety of other applications as well as some basic natural language processing techniques.  These include: a) digitization (utf 8), b) removal of stopwords, numbers, punctuation, c) tokenization, d) calculation of word frequencies / proportions, e) part of speech tagging, and f) concordan

May 2, 2018
Coordinator:
Hoda Magid

R FUN!damentals Part 2: Subsetting and Reshaping

May 1, 2018
Coordinator:
Stacy Reardon

You've invested a lot of work in creating a digital project, but how do you ensure it has staying power? We'll look at choices you can make at the beginning of project development to influence sustainability, best practices for documentation and asset management, and how to sunset your project in a way that ensures long-term access for future researchers.

May 1, 2018
Coordinator:
Josué Meléndez Rodríguez

This workshop will introduce participants to the use of qualitative data analysis (QDA) software and provide an overview of popular programs. This workshop is ideal for researchers who are new to the idea of using QDA software.

May 1, 2018
Coordinator:
Soumya Gupta

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 1 Topics:

May 1, 2018
Coordinator:
Geoff Bacon

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.

May 1, 2018
Coordinator:
Patty Frontiera

Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into a research project. 

Geospatial Data in R, part 2: Geoprocessing and analysis

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