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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-Jul-18
E.g., 19-Jul-18
April 6, 2018
Coordinator:
Kimberly Rubens

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.

Workshop: MAX QDA
April 5, 2018
Coordinator:
Claudia von Vacano

MAX QDA GSE

April 4, 2018
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, two-part workshop.

Knowledge Requirements: No prerequisites

April 4, 2018
Coordinator:
Hoda Magid

This three-part series will cover the following materials:

Part 1:  Introduction

April 3, 2018
Coordinator:
Geoff Bacon, 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 1 Topics:

April 2, 2018
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, two-part workshop.

Knowledge Requirements: No prerequisites

April 2, 2018
Coordinator:
Evan Muzzall

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.

March 23, 2018
Coordinator:
Chris Gagne

This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets.

March 23, 2018
Coordinator:
Geoff Bacon

This workshop addresses various topics in Natural Language Processing, primarily through the use of NLTK. We'll work with a corpus of documents and learn how to identify different types of linguistic structure in the text, which can help in classifying the documents or extracting useful information from them.

March 22, 2018
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.

March 22, 2018
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.

March 21, 2018
Coordinator:
Soumya Gupta

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:

March 21, 2018
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.

March 21, 2018
Coordinator:
Susan Powell

Building on the "Georectifying Historical Maps" workshop, the next step in creating useable GIS data from historical map sources often involves digitizing features to create new vector layers. This workshop will introduce the basic concepts and best-practices of feature digitization. We'll explore the tools and processes through a hands-on exercise.

March 20, 2018
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.

March 20, 2018
Coordinator:
Isabelle Cohen

This three-part series will cover the following materials:

Part 1:  Introduction

March 19, 2018
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.

March 19, 2018
Coordinator:
Geoff Bacon

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.

March 19, 2018
Coordinator:
Kari Peterson

Join Kari Peterson, Associate Director of Data Analysis at Haas Development & Alumni Relations and founder of the Cal Data Visualization Network, for this workshop on best practices for communicating your data visually. We'll be covering terminology, color theory, how to pick a viz, tips for how to make sure your viz says what you want it to say, and more.

March 19, 2018
Coordinator:
Soumya Gupta

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:

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