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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., 20-Nov-17
E.g., 20-Nov-17
May 18, 2017
Coordinator:
Scott McGinnis

This four-part intensive will introduce a suite of related technologies, centered on XML, for working with structured texts and data.  The course begins by introducing basic concepts with an exercise in creating an HTML webpage.  After that, it will move to cover several important XML applications, with exercises in dynamic mapping (with KML) and structured markup of literary and historical tex

May 17, 2017
Coordinator:
Scott McGinnis

This four-part intensive will introduce a suite of related technologies, centered on XML, for working with structured texts and data.  The course begins by introducing basic concepts with an exercise in creating an HTML webpage.  After that, it will move to cover several important XML applications, with exercises in dynamic mapping (with KML) and structured markup of literary and historical tex

May 16, 2017
Coordinator:
Scott McGinnis

This four-part intensive will introduce a suite of related technologies, centered on XML, for working with structured texts and data.  The course begins by introducing basic concepts with an exercise in creating an HTML webpage.  After that, it will move to cover several important XML applications, with exercises in dynamic mapping (with KML) and structured markup of literary and historical tex

May 11, 2017
Coordinator:
Daniela Vargas Mallard

This two-part series will focus on how to set up database-like structures, navigate them, create models and build various types of reports in Microsoft Excel. By the end of this series, participants will be able to sort and look for information within large datasets, use character-based functions, pivot tables, and build basic financial models.

May 11, 2017
Coordinator:
Nora Broege

This two-part workshop provides an introduction to both quantitative and qualitative social science methods.

May 11, 2017
Coordinator:
Ben Gebre-Medhin

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 10, 2017
Coordinator:
Daniela Vargas Mallard

This two-part series will focus on how to set up database-like structures, navigate them, create models and build various types of reports in Microsoft Excel. By the end of this series, participants will be able to sort and look for information within large datasets, use character-based functions, pivot tables, and build basic financial models.

May 10, 2017
Coordinator:
Ben Gebre-Medhin

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 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.

May 9, 2017
Coordinator:
Sean Freeder

This workshop will introduce students to the basics of designing a survey instrument using the Qualtrics platform, such as randomization and survey flow. We will also cover more advanced topics like implementing embedded data and using javascript, as well as tips and tricks on how to use your design to maximize the number of quality responses you get.

May 9, 2017
Coordinator:
Ben Gebre-Medhin

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 9, 2017
Coordinator:
Nora Broege

This two-part workshop provides an introduction to both quantitative and qualitative social science methods.

May 8, 2017
Coordinator:
Adam Anderson

In this workshop, we will begin with a dataset scraped from Twitter, which came from the hashtag March4Trump during the rally in Berkeley. Next we will structure our data in Jupyter Notebooks in order to visualize it using social network analysis in Gephi. We will finish by running statistical analysis and discussing implications and questions.

May 8, 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.

May 5, 2017
Coordinator:
Rachel Jansen

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 5, 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!

May 5, 2017
Coordinator:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction (Tuesday, May 2)

May 4, 2017
Coordinator:
Rachel Jansen

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 4, 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!

May 4, 2017
Coordinator:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction (Tuesday, May 2)

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