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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., 19-Apr-18
E.g., 19-Apr-18
November 8, 2017
Coordinator:
Chris Gagne

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:

November 8, 2017
Coordinator:
Evan Muzzall

R FUN!damentals Part 2: Subsetting and Reshaping

November 7, 2017

This workshop has been cancelled. The workshop will be offered again during RRR week. Stay tuned for details. Our most sincere apologies for any inconvenience.

November 7, 2017
Coordinator:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction

November 6, 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:

November 1, 2017
Coordinator:
Josh Quan

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.

November 1, 2017
Coordinator:
Ariana Thompson-Lastad

Join D-Lab for a conversation with Ariana Thompson-Lastad, a PhD Candidate at the UC San Francisco Department of Social and Behavioral Sciences and Affiliated Graduate Student with the UC Berkeley Institute for the Study of Societal Issues. Ariana is currently writing her mixed-methods dissertation, which uses interviews, observations, and a self-designed survey.

November 1, 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!

November 1, 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.

October 31, 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.

October 30, 2017
Coordinator:
Josh Quan

This workshop will provide a comprehensive overview of graphics in R, including base graphics and ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data.

October 27, 2017
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

October 26, 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.

October 26, 2017
Coordinator:
Thomas L. Piazza

This workshop is Part 2 of a two-part series on survey sampling. Multi-stage sampling is required when a complete list of the target sampling units (persons or households) is unavailable or too expensive to assemble. This workshop will discuss how to select units in stages so that the final sample is a probability sample of the defined population.

October 25, 2017
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. By the end of both sections, students will be able to employ Excel skills to open source policy data sets. These skills are transferrable to any sector.

Topics Covered Will Include:

October 25, 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.

October 24, 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 3 Topics:

October 24, 2017
Coordinator:
Thomas L. Piazza

This workshop is the first part of a two-part series on survey sampling. This first workshop will cover the basic principles and methods of sampling. Topics will include a discussion of the various types of samples, the creation of sampling frames, the use of stratification, and basic methods of selecting samples.

October 24, 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.

October 23, 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.

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