Additional workshop information will be made available in mid-September. For now, see the Statistical Software box for current Fall offerings.
For workshops in chronological order click here.
See below for workshops by topic.
Additional workshops on High Performance Computing are offered by OARC. See their calendar and resources for more information.
These workshops are open to all without registration.
Bring your own laptop to these sessions to get the most out of them!
Later in the semester, there are plans to repeat these as webinars (schedule to come in late September).
Introduction to SAS
This workshop provides an introduction to SAS, covering the basics of navigation, loading data, graphics, and elementary descriptive statistics and regression using a sample dataset.
SAS is a powerful and long-standing system that handles large data sets well, and is popular in the pharmaceutical industry and health sciences, among other applications.
R for data analysis: a tidyverse approach 
The session introduces the R statistical software environment and basic methods of data analysis, and also introduces the "tidyverse". While R is much more than the "tidyverse", the development of the "tidyverse" set of packages, led by RStudio, has provided a powerful and connected toolkit to get started with using R. Note that graphics and data manipulation are covered in subsequent sessions.
R graphics with ggplot2 
The ggplot2 package from the tidyverse provides extensive and flexible graphical capabilities within a consistent framework. This session introduces the main features of ggplot2. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background.
R data wrangling with dplyr, tidyr, readr and more 
Some of the most powerful features of the tidyverse relate to its abilities to import, filter, and otherwise manipulate data. This session reviews major packages within the tidyverse that relate to the essential data handling steps require before (and during) data analysis.
R for interactivity: an introduction to Shiny 
Shiny is an R package that enables the creation of interactive websites for data visualization. This session provides a brief overview of the Shiny framework, and how to edit and publish Shiny sites in RStudio (with shinyapps.io). Familiarity with R/RStudio is assumed.
R for reproducible scientific documents: knitr, rmarkdown, and beyond 
The RStudio environment enables the easy creation of documents in various formats (HTML, DOC, PDF) using Rmarkdown, while knitr allows the incorporation of executable R code to produce the tables and figures in those documents. This session introduces these concepts and other packages and practices supporting reproducibility with the R environment.
Also see the Digital Humanities workshops above for several workshops involving R.
Additional workshop information will be made available in mid-September. For now, see the Statistical Software box for current Fall offerings. We expect to offer workshops similar to those offered during the last academic year, described below.
Open Science with Github and Git
Scientists are frequently required to share the products of their funded research. Learn how to use the freely available Github platform for project management and collaboration, and connect your Github project to the open Zenodo repository to share your work, and make it citable with a permanent Digital Object Identifier (DOI). No previous experience is necessary.
Introduction to Github and Git
This workshop will introduce participants to the open code sharing platform Github, and explore commonly used functions in Github and Git. The first 45 minutes will be introductory, and will continue with slightly more advanced functions in the second half. No previous experience is necessary, and please bring your own laptop.
Additional workshop information will be made available in mid-September. For now, see the Statistical Software box for current Fall offerings. We expect to offer workshops similar to those offered during the last academic year, described below.
Workshops are offered in either Alexander Library or LSM (with identical content). Participants in LSM-based workshops must bring their own laptops. At Alexander, you can either bring your own laptop, or use the desktops in the lab.
Python Basics and Data Exploration
This workshop will be an accelerated introduction to fundamental concepts such as variable assignment, data types, basic calculations, working with strings and lists, control structures (e.g. for-loops), functions. We will also start working with pandas, a popular data science library in Python, to explore a dataset on foodborne outbreaks reported to the CDC.
Data Manipulation and Analysis with Python
In this workshop, we will dive into the world of arrays and data frames using the NumPy and pandas libraries. We'll cover data cleaning and pre-processing, joining and merging, group operations, and more. If you work with tabular data, this workshop is for you!
Data Visualization and Machine Learning with Python
Interested in finding patterns and predicting unknown attribute values in your data? Join us for an overview of machine learning techniques implemented using the scikit-learn library. We'll also learn how to do data visualization with matplotlib, a popular plotting library in Python.
Data Scraping: Interaction with APIs with Python
This workshop is intended to show how to use Python to interact with third-party APIs for data collection. Different type of APIs with real applications will be introduced. Examples such as Rest API for FRED and Quandl will be discussed. A project regarding interacting with FRED API and merging with historical data will be demonstrated in detail.
Data Mining: Regression and Classification with Python
The traditional Least Square estimation, KNN face severe overfitting issues when the dataset has high-dimensional features. Modern data mining regression techniques such as lasso and classification techniques such as SVM gives a better estimation result in such a situation. The workshop intends to show how lasso and SVM works in Python. Compare the estimation result of Lasso with least square estimation, SVM with KNN in the high-dimensional setting.
Additional workshop information will be made available in mid-September. For now, see the Statistical Software box for current Fall offerings. We expect to offer workshops similar to those offered during the last academic year, described below.
Introduction to NVivo
This workshop is intended as a basic introduction to using NVivo, a software that supports qualitative and mixed methods research. The workshop focuses on introducing key mechanisms of the software that may be applied as required by different analytical approaches.
Advanced NVivo: Data Visualizations Using NVivo 12
This workshop focuses on the introduction of a suite of visualizations that help you gain deeper insights from your data by exploring and unearthing patterns, trends and connections.
Citation Management with Zotero
Zotero is a free application that collects, manages, and formats citations and bibliographies. In this introductory, hands-on workshop, we’ll learn how to organize sources, attach PDFs and notes, create tags for easy searching, and generate citations and bibliographies in Word. Bring your personal laptop, download Zotero 5.0 for your OS, and the Zotero Connector for your favorite browser.
Thematic Maps in QGIS
Thematic maps show one or more themes (or variables) arranged spatially on a map. In this workshop, we’ll explore the basic building blocks of geospatial visualizations, including data types, file formats, and some ways of representing data, using a free and open source GIS called QGIS.
Georeferencing Historical Maps in QGIS
Georeferencing is the process of assigning real world map coordinates to a two dimensional image or raster. This technique allows researchers to take an historic map and plot it in modern mapping software, such as QGIS. In this workshop, we will explore two different methods of using raster imagery in historical GIS.
Additional workshop information will be made available in mid-September.
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