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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-Oct-20
E.g., 20-Oct-20
March 11, 2020
Author:
Aniket Kesari
March 9, 2020
Author:
Aniket Kesari

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:

March 6, 2020

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.

March 6, 2020
Author:
Juliet Flores Wilson

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.

March 5, 2020
Author:
Gloria Ashaolu

The Black Recruitment and Retention Center is a student initiated, AND entirely a student ran organization that was founded in 1983 as direct response to the removal of Black students from affirmative action policies and programs, including admissions consideration, early academic outreach programs, and retention services. 

 

Workshop: Tableau Bootcamp
March 5, 2020
Author:
Kari Peterson, Juliet Bonczkowski

Add data visualization to your communication toolbox without learning to code. Tableau cuts down the time you need to spend creating visualizations through an intuitive graphical user interface. Learn the basics in this hands-on workshop.

  • No prerequisites

March 3, 2020
Author:
Michael Sholinbeck

Participants in this workshop will learn about some of the issues surrounding the collection of health statistics, and will also learn about authoritative sources of health statistics and data. We will look at tools that let you create custom tables of vital statistics (birth, death, etc.), disease statistics, health behavior statistics, and more. The focus will be on U.S.

March 3, 2020
Author:
Ann Glusker

In Visualization in Excel, we will cover the fundamentals of visualization in Excel, including a checklist of considerations that should go into every visualization. We will also go through step by step instructions on how to make horizontal bar charts, slope graphs, butterfly charts, the good kind of pie charts, icon arrays, and how to graph confidence intervals.

March 2, 2020
Author:
Drew Hart

This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups.

February 27, 2020
Author:
Isabelle Cohen, Maura Lievano

LaTeX is a widely used document creation software which can help you improve the presentation of homework, papers, academic articles and even presentations.

Workshop: Weighting Data
February 27, 2020
Author:
Thomas L. Piazza

This workshop will cover the main types of weighting, to correct for bias in sample data.

February 26, 2020
Author:
Adam G. Anderson, Stacy Reardon

The Berkeley Digital Humanities Working Group began in 2011 as a place to facilitate interdisciplinary conversations around topics in the Digital Humanities (broadly defined).  We welcome participants from all disciplinary backgrounds, beginners and experts in digital skills, students, faculty, and staff.  The agenda for our biweekly meetings is participant driven, and we typically h

February 26, 2020
Author:
Emily Grabowski

This workshop introduces Artificial Neural Networks (ANNs), a group of popular machine learning algorithms. No prior knowledge is required, though previous experience with other machine learning algorithms would be helpful. The workshop will be divided into 3 parts:

February 26, 2020
Author:
Ann Glusker

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.

February 26, 2020
Author:
Aniket Kesari, Renata Barreto

For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter (formerly IPython) notebook. The following plot types will be covered:

February 25, 2020
Author:
Isabelle Cohen, Maura Lievano

LaTeX is a widely used document creation software which can help you improve the presentation of homework, papers, academic articles and even presentations.

February 25, 2020
Author:
Chris Kennedy

This workshop introduces the basic concepts of Deep Learning - the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data.

February 24, 2020
Author:
Drew Hart

It is often said that 80% of data analysis is spent on the process of cleaning and preparing the data. This workshop will introduce tools (notably dplyr and tidyr) that makes data wrangling and manipulation much easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful stuff.

February 24, 2020
Author:
Drew Hart

It is often said that 80% of data analysis is spent on the process of cleaning and preparing the data. This workshop will introduce tools (notably dplyr and tidyr) that makes data wrangling and manipulation much easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful stuff.

February 24, 2020
Author:
Aniket Kesari, Renata Barreto

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:

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