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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., 24-Nov-17
E.g., 24-Nov-17
October 18, 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

October 17, 2017

Join Ann Rose, from QSR International, as she facilitates an informal gathering of Berkeley researchers to view a demonstration of NVivo software, ask questions, provide feedback as to their needs for qualitative and mixed-methods research software, and connect with other NVivo users on campus.

October 17, 2017
Coordinator:
Alex Estes

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:

October 17, 2017
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.

October 16, 2017
Coordinator:
Isabelle Cohen

This three-part series will cover the following materials:

Part 1:  Introduction

October 11, 2017
Coordinator:
Celia Emmelhainz

This workshop outlines how to organize and then code qualitative research materials in ATLAS.ti. Attendees will first discuss the decisions to make before importing text, audio, or video into the software program, and then review how to start a project, import documents, apply codes, and run initial analyses. There will be time for questions and answers at the end.

October 11, 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.

October 11, 2017
Coordinator:
Susan Powell

This workshop will introduce two different web platforms for exploring and mapping U.S. demographic data: SimplyAnalytics and PolicyMap. While there is some overlap between the different applications, each has its own strengths and unique features. For each platform we will walk through a short demo, followed by some time to explore the data and visualization tools that each platform offers.

October 10, 2017
Coordinator:
Alex Estes

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:

October 10, 2017
Coordinator:
Evan Muzzall

R FUN!damentals Part 2: Subsetting and Reshaping

October 9, 2017
Coordinator:
Alex Estes

Please note: This is a three-part workshop series. The first session will occur Monday, October 2 from 1:00-4:00pm. The second session will occur Monday, October 9 from 1:00-4:00pm. The third session will occur Monday, October 23 from 1:00-4:00pm.

October 9, 2017
Coordinator:
Isabelle Cohen

This three-part series will cover the following materials:

Part 1:  Introduction

October 5, 2017
Coordinator:
Kari Peterson

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.

October 4, 2017
Coordinator:
Geoff Bacon

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.

October 4, 2017
Coordinator:
Patty Frontiera

In this hands-on workshop participants will create maps of geographic data. Participants will build on their knowledge of R to create static maps with ggplot2. We will then practice adding reference maps, or basemaps, to the static maps using ggmap. Finally, we introduce the leafletR package for creating interactive data maps.

October 3, 2017
Coordinator:
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.

October 3, 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!

October 2, 2017
Coordinator:
Alex Estes

Please note: This is a three-part workshop series. The first session will occur Monday, October 2 from 1:00-4:00pm. The second session will occur Monday, October 9 from 1:00-4:00pm. The third session will occur Monday, October 23 from 1:00-4:00pm.

October 2, 2017
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.

September 29, 2017
Coordinator:
Chris Gagne

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