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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-Apr-25
E.g., 23-Apr-25
September 5, 2017
Author:
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!

September 1, 2017
Author:
Samy Abdel-Ghaffar

An intro to the basics that instructors often assume you know, but that you probably never had good instruction on! After this course, you should be able to more easily start learning to program (e.g., in our R or Python Fundamentals series), follow instructions and documentation online (e.g., StackExchange), and communicate better with your collaborators who are programming.

August 31, 2017
Author:
Nancy Thomas, Patty Frontiera
August 22, 2017
Author:
Josué Meléndez Rodríguez

This workshop will provide an overview of popular QDA software (i.e., NVivo, MaxQDA, Dedoose, and Atlas.TI), including a review of similarities and differences. This workshop is ideal for researchers who are new to QDA software. More advanced workshops will be offered throughout the semester.

August 22, 2017
Author:
Zawadi Rucks-Ahidiana

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 MaxQDA project and engage in the following tasks: set up a database, use folders, add codes, add document variables, conduct queries, and explore data for further analysis.

 

August 21, 2017
Author:
Kenly Brown

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 reviews how to start a new Dedoose project and engage in the following tasks: add codes, set up a code system, code data, add characteristics about data, run analysis tools, and explore data for further analysis.

August 21, 2017
Author:
Shelly Steward

Through this workshop, attendees will explore the process of moving from coded qualitative data to conclusions. Attendees will explore the logic of analysis, identification of relationships in data, and building of arguments with data.

Workshop: R Bootcamp 2017
August 19, 2017
Author:
Christopher Paciorek

The workshop will be an intensive two-day introduction to R using RStudio. Topics will include

August 18, 2017

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.

August 18, 2017
Author:
Ben Gebre-Medhin

Part 3: Unsupervised Approaches (12-2pm)

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.

August 18, 2017
Author:
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!

August 18, 2017
Author:
Isabelle Cohen

This workshop will focus on how to create publication-ready graphs using Stata. We will begin with a short demo of how to create standard graphs in Stata, and continue on to more high-quality formats for greater legibility and a more polished display.

August 18, 2017
Author:
Shelly Steward, Josué Meléndez Rodríguez

This culminating event will engage attendees in a review, reflection, and discussion about the topics covered in the week-long series of workshops offered under the title "Introduction to Qualitative Research: Philosophy to Analysis." This event is designed for those who plan to attend all (or most) workshops in the series (available for registration via D-Lab's website). Specific activities wi

August 17, 2017
Author:
Shelly Steward

This intermediate workshop expands on an introductory workshop offered on the same software. The training will review how to engage in more advanced tasks, and how to begin moving from coding to making conclusions with the data.

August 17, 2017
Author:
Ben Gebre-Medhin

Part 1: Methods and Approaches (12-2pm)

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.

August 17, 2017
Author:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction (Tuesday, August 15)

August 17, 2017
Author:
Shelly Steward

This introductory workshop focuses on how to organize and code qualitative data in ATLAS.ti. 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.

August 16, 2017
Author:
Shelly Steward

This workshop will provide an overview of popular qualitative data analysis (QDA) software (i.e., NVivo, MaxQDA, Dedoose, and Atlas.TI), including a review of similarities and differences between them. This workshop is ideal for researchers who are new to QDA software. More advanced workshops will be offered in the days after this introduction, as well as throughout the semester.

August 16, 2017

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:

August 16, 2017
Author:
Samy Abdel-Ghaffar

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!

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