In response to the COVID-19 situation, all workshops will be moved online for the period after Spring Break.
Current information about online (Webex-based) workshops is posted here, with Webex links to workshops made available as they are created. The situation is changing daily, so please register for workshops of interest to receive updated information and reminders.
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.
The New Brunswick Libraries Science Workshop Series also offers instruction in citation metrics, Web of Science, Scopus, and EndNote
There are two separate series of Python workshops, with different instructors and different content. Prior to Spring Break, Sly (Ziqiu) Zhong will teach her series at the Library of Science and Medicine, and Sanket Badhe will teach his series at Alexander Library. After Spring Break, each instructor will run their series again, switching locations. Sly Zhong's series is more geared to beginners with the language (labeled "Beginners"), while Sanket Badhe's series will move at a faster pace (labeled "Accelerated").
☞ RSVP for any/all of the Python workshops.
Python Basics and Data Exploration (Accelerated 1)
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.
Python Basics and Data Exploration (Beginners 1)
This workshop will be a more deliberate introduction to fundamental concepts such as variable assignment, data types, basic calculations, working with strings and lists, control structures (e.g. for-loops), functions.
Cryptocurrency API, Visualization, and Comparison project
Data Manipulation and Analysis with Python (Accelerated 2)
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 Manipulation and Analysis with Python (Beginners 2)
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.
Statistical Hypothesis Tests - Basic Concepts and Implementation
This workshop delves into a wider variety of basic and most commonly used statistical tests including Null Hypothesis Testing, Critical Value, p-value, Z-test, T-test and Chi-Square Test etc. We will also introduce some examples about how to implement those tests with given database.
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 Visualization (Beginners 3)
This workshop will continue with Numpy and Panda libraries. Data visualization with matplotlib, a popular plotting library in Python, will also be covered. Turn data into line, bar, scatter plots etc. Environmental Science and Economics data will be used and examples.scikit-learn library. We'll also learn how to do data visualization with matplotlib, a popular plotting library in Python.
Intro to Tableau 1
The workshop will introduce the basics of using Tableau for Data Visualization. Design principles of quantitative and qualitive presenting and meaningful display methods.
Statistical Inference with Python
In this workshop, we will explore basic principles behind using data for estimation and for assessing theories. The workshop will focus on inference procedures, constructing confidence intervals, and hypothesis testing.
Data Science with Python, part 1
This workshop delves into a wider variety of basic supervised learning methods for both classification and regression (Linear Regression, Logistic Regression, Naive Bayes, k-nearest neighbor). In the last part, we will discuss unsupervised learning techniques namely k-Means, PCA. We will apply all techniques on a dataset and compare each of these techniques in terms of accuracy, inference, etc.
Exercise and Practice in Python (Beginner 4)
This workshop will go over some exercises and practice questions using Python for beginners. If you’re starting out with Python, this workshop is a good way to test your knowledge and learn how to make some small programs.
Intro to Tableau 2
More Tableau functions and data visualization options will be covered in this workshop.
Data Science with Python, part 2
This workshop focuses on advanced supervised learning methods for both classification and regression (Decision Tree, Random Forest, Support Vector Machine, Ensemble learning, Neural Network). We will apply all these techniques on a dataset and compare the results of each technique.
Neural Networks
This workshop describe Neural Network techniques for data analysis.
Interaction with API in Economics
An API, or application programming interface, is a common tool for interacting with data on the web. This workshop will present how APIs are used in Finance (Equity and Cryptocurrency) and Economics (FRED) industry.Cryptocurrency) and Economics (FRED) industry.
Statistical Hypothesis Tests in Python/SAS/R
This workshop will introduce how to run most commonly used statistical tests in different programming languages including Python and R and show comparison of each of the languages.
Spark Introduction
This workshop will introduce you to pyspark, its features and components.
☞ RSVP for any/all of the Python workshops.
☞RSVP for R (and SAS) workshop series.
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 series for several workshops involving R.
☞RSVP for R (and SAS) workshop series.
Introduction to NVivo
☞ RSVP for the Qualitative Data/NVivo workshops
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.
Qualitative Methods Applications
This workshop introduces hands on practical techniques of how to plan out and conduct small scale pilot studies. This session will provide an overview of how to create a realistic timeline for a study which includes selecting participants, practical approaches on how to managing sensitive /difficult subjects, and how to ethically and critically connect theory to qualitative analysis using NVivo.ging sensitive /difficult subjects, and how to ethically and critically connect theory to qualitative analysis using NVivo.
☞ RSVP for the Qualitative Data/NVivo workshops
PROVIDE FEEDBACK FOR NVIVO WORKSHOPS HERE
☞ RSVP at https://go.rutgers.edu/cq7y8muq
Introduction to Quantitative Text Analysis
This hands-on workshop will introduce participants to the basics of quantitative textual analysis using the R programming language. Participants will each first select a text of their choice from Project Gutenberg (literary or otherwise), which we will then explore through the demonstration of a variety of approaches, including word frequency, distribution, and co-appearance. No coding experience required.
This workshop is the first in a two-part series on social media data. Twitter data provide researchers with a real-time view into a wide variety of social and cultural topics. In this workshop, we’ll explore beginning and intermediate tools for collecting social media data from Twitter.
This workshop is the second of a two-part series. In this workshop, we’ll receive a gentle introduction to the R language and RStudio, the most commonly used integrated development environment for R. We’ll explore a social media dataset using some popular packages of the tidyverse collection, including dplyr and ggplot2.
Network Analysis in Gephi
Network analysis is one of the most popular approaches in the digital humanities because it allows us to model relations–between individuals, texts, locations, and more. In this workshop, participants will be introduced to the central concepts of network analysis before learning how to use Gephi, one of the most popular programs for analyzing and visualizing networks.
Approaches to Web Scraping in R
An ever-growing wealth of information can be accessed online, but often there is no easy way to obtain this information for further analysis. This hands-on workshop will introduce a solution to this problem: web scraping, a technique for extracting data and data structures from public websites. Using our browsers and the R programming language, we’ll also explore strategies for handling different kinds of websites. No previous coding experience required.
Introduction to Scalar
In this workshop, we will introduce the use of Scalar, a web publishing platform for digital scholarship which supports individual and collaborative projects featuring tagging functionalities, analysis and annotation of images, maps, audio and video files, as well as visualizations.
Using Palladio for Mapping
Palladio is a web-based tool for investigating and visualizing multi-dimensional data. In this workshop, we will learn to visualize humanistic research data on a map, and track connections between data points.
Making Websites with Hugo and GitHub Pages
Personal and project websites can be effective vehicles for sharing your research. In this workshop we'll learn to use Hugo, an open-source static site generator, to build a website locally by editing themes and adding original content. We'll also learn how to deploy the result with free hosting on GitHub Pages. In the process, participants will gain some experience with HTML, Git, and the command line. Previous knowledge of any of these will help but is not necessary; a personal computer on which you have admin privileges, however, is required.
Word Vectors and Text Analysis
This workshop introduces the Women Writers Vector Toolkit, an interface that allows researchers to conduct word vector analyses on texts already available in the Women Writers Project (works authored by women from 1400 to 1850). Word embedding models are a type of text analysis used to explore larger thematic questions about extensive collections of texts. Through this method, computational tools display spatial analogies, thus representing relationships between words.
Editing in QGIS
Learn about the advanced editing toolbar in QGIS. This workshop will show you how to use advanced editing tools to improve the accuracy of your layers, and digitize data more efficiently. Tools that we will talk about in this workshop will not only help you create new GIS layers, but will also help you correct existing GIS layers. We will learn more about digitizing through a hands-on exercise in class.
Webex Meeting information:
Meeting number: 791 763 321
Password: WktDmbMv543
https://rutgers.webex.com/rutgers/j.php?MTID=m5f03676ef3baa67c0fcb529168f6bc89
Join by video system
Dial 791763321@rutgers.webex.com
You can also dial 173.243.2.68 and enter your meeting number.
Please register to attend at https://tinyurl.com/GIS-LSM
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Past Workshops
Introduction to GIS with QGIS
This will be an introductory workshop, no prior GIS knowledge is needed. In this workshop, we will present the basic concepts of Geographic Information Systems. We will discuss file formats, data types, open source data, basic data visualization, attribute tables, projections, and coordinate systems. Time permitting, we will also learn about thematic maps and data classification, and we will explore and interpret some aspects of cartography, such as map layout, text, and color. We will be using QGIS, a freely available GIS application. Please bring a laptop. If you don’t have one, some laptops will be available to borrow.
Please register to attend at https://tinyurl.com/GIS-LSM
Advanced GIS with QGIS
In this workshop, we will learn about selection, queries, and spatial joins; and we will cover geoprocessing tools such as dissolve, merge, append, clip, buffer, intersect, union, and erase. We will present address geocoding, and working with street files. Time permitting we will discuss digitizing paper maps, and how to create shapefiles, geoeferencing, and using the editing toolbar. Some prior familiarity with GIS is assumed. We will be using QGIS, a freely available GIS application. Please bring a laptop. If you don’t have one, some laptops will be available to borrow.
Please register to attend at https://tinyurl.com/GIS-LSM
Raster Analysis Using QGIS
This workshop will teach you how to use and analyze data from remote sensing satellites. Learn how to analyze raster data using the spatial analyst extension in QGIS. We will present raster analysis, raster calculator, vector to raster conversion, raster calculator, reclassify, hillshade analysis, contours, slope, aspect, viewshade analysis, cut-fill analysis, and distance function and analysis.
Please register to attend at https://tinyurl.com/GIS-LSM
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