Introduction to GIS with QGIS
November 6, Library of Science and Medicine, 1:30-3:30 pm
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
November 13, Library of Science and Medicine, 1:30-3:30 pm
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
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.
☞ RSVP for the Python workshops.
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.
Python in Industry - Cryptocurrency Comparison Project
☞ RSVP for the Python workshops.
Utilizing numpy, pandas and matplotlib, this workshop will show how to make a program that can compare the price, Log Returns, SMA (Simple Moving Average) of Bitcoin and Ethereum, and predict which one is a better investment choice with Python.
Data Science with Python, part 1
☞ RSVP for the Python workshops.
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.
Data Science with Python, part 2
☞ RSVP for the Python workshops.
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.
-----------------------------------------------------
PAST WORKSHOPS
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.
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.
These workshops are open to all without registration.
Bring your own laptop to these sessions to get the most out of them!
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.
Introduction to NVivo
☞ RSVP for the 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.
☞ RSVP for the NVivo workshops
PROVIDE FEEDBACK FOR NVIVO WORKSHOPS HERE
☛ RSVP at http://go.rutgers.edu/11x2vbxi
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.
The biggest initial hurdle to using DH methods in one’s own work is finding usable materials in the first place. This workshop is designed to help identify potential data in the wild of humanistic sources and how to translate it into usable formats. We’ll explore specific practices like transcribing archival materials into spreadsheets and turning HathiTrust texts into clean .txt files. We’ll also survey examples from existing scholarship to demonstrate some possible uses of these kinds of data as well as weigh the costs and benefits of translating sources into data.
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.
So you’ve finally assembled or gotten your hands on a dataset or spreadsheet. Nice work! Not sure what to do next? This hour-long workshop will provide strategies for efficiently turning semi-structured data into tidy data before introducing participants to a range of simple but powerful analyses using the R programming language. No coding experience required. Participants are encouraged (but not required) to bring their own datasets to work with, and all are welcome to stay afterwards for an open office hour to discuss any further or more specific questions.
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.
This workshop is the first of two exploring the recently added New Jersey newspapers in Chronicling America. In this first part, we’ll focus on techniques and strategies for fuzzy string matching in the R programming language, using the OCR-derived text from the Perth Amboy Evening News. Anyone interested in fuzzy string matching or textual analysis of mass print is encouraged to attend.
This workshop is the second of two exploring the recently added New Jersey newspapers in Chronicling America. In the second part, we’ll begin with the results of the previous workshop and do some basic analysis of phrase use over time, frequency, and collocate words. Anyone interested in fuzzy string matching or textual analysis of mass print is encouraged to attend; attendance of part one is encouraged but not necessary.
Curious about the latest developments in digital textual studies? Would you like to learn about existing and ongoing digital editions undertaken by scholars at Rutgers and beyond? This workshop will provide a hands-on introduction to the theory and practice of encoding literary and historical texts for the humanities. This workshop is designed for people considering starting a digital project using primary sources, or who would like to understand the concepts of text markup using the Text Encoding Initiative (TEI) Guidelines. RSVP to fg162 [AT] rutgers.edu
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.
Rutgers, The State University of New Jersey, an equal access/equal opportunity institution. Individuals with disabilities are encouraged to direct suggestions, comments, or complaints concerning any accessibility issues with Rutgers web sites to: accessibility@rutgers.edu or complete the Report Accessibility Barrier / Provide Feedback Form.
Hours
My Account
Ask Us
