Summer 2024 FORC Offering: August 28-30 

FORC 2024 was a success! Check back soon for new offerings.

Overview

The Foundations of Research Computing (FORC) Camp is a three day data skills immersion program offered to Arts & Science Master’s College students by Data Services (NYU Libraries and IT) in collaboration with the Arts & Science Office of Teaching Excellence and Innovation. FORC will give participants a thorough grounding in the digital skills essential for their research. There is something for every disciplinary approach, from creating visualizations that require no coding skills to data harvesting and statistical analysis. Choose the track that is right for your needs – in the Project Examples sections, we’ve included links to research projects NYU graduate students have worked on using the skills covered in each track. 

Each day’s schedule will include two to four hours of interactive instruction followed by a 90 minute office hours/tea time that offers opportunities for one on one consults, meeting with subject area librarians, and building connections with your graduate student colleagues. An optional 90 minutes of homework will allow you to apply digital skills to your own research for feedback from FORC instructors. 

Participants who complete all 10 hours of the FORC curriculum will receive a letter of completion for their portfolio detailing the skills covered in their track. 

Send inquiries to asteaching@nyu.edu. 

Track One: Telling Stories with Data (Non-Coding)

Description

If your research trajectory doesn’t require you to learn coding, but you still want to be able to create, analyze, and display data sets using methods like mapping, text searching, visualization, and digital repositories, this is the track for you. We'll look at ways to incorporate digital storytelling and the different types of software platforms available to visualize your research data. See full Track One details here.

Project Examples 

Here is a sampling of projects NYU graduate students have worked on using the types of skills covered in this track: 

Creating Interactive Maps:  Mapping Artistic Activism Project (MAAP), 

Building Digital Displays from Archives: Visualizing the Victorian Polar Network 

Assembling a text corpus: Digitizing Chemical Humanities, 

Creating Data Visualizations: Insuring Slavery: Underwriting Risk in the 18th Century

Building Website Repository for Research Artifacts: Archive of Cuban Socialism. 

Track Two: Intro to Coding: Practical Python for Research Applications

Description

If you’re ready to get out of Excel and learn some simple coding functions to assemble, analyze, and display research data, this is the track for you. Participants will learn how to use basic Python to automate tasks and harvest and manipulate data. This track also will get you ready should you want to learn more robust coding in the future (whether Python or options like R or Javascript). See full Track Two details here.

Project Examples

Here is a sampling of projects NYU graduate students have worked on using the types of skills covered in this track:

Extraction of Word Embeddings from a Corpus: Framing Democracy: Characterizing China's Negative Legitimation Propaganda using Word Embeddings

Automated extraction of semantic motifs from a large text corpus: Who Kisses Whom: Gendered Interaction in American Novels 1880-2000

DH Project using Python/Flask: Demystifying the Digitization of Texts: New Textual Analysis for the Medieval History of Islamic Mysticism, A Corpus of Digitally Neglected Texts 

Track Three: Advancing Your Quantitative Analysis Skills Using R

Description 

If your research will involve statistical analysis of data, this track will give you the thorough grounding in R required for your graduate work. This course is useful even for those who have dabbled in R before, because it provides the foundational skills that will allow you to easily move on to more advanced applications and ensure your mastery of research essentials such as reproducibility. See full Track Three details here.

Project Examples

Here is a sampling of projects NYU graduate students have worked on using the types of skills covered in this track:

Analysis of a publicly available data set: Do Black & LatinX Students in NYC Have Equal Access to Computer Science Instruction? 

Data Set Creation and Text Analysis: Uncovering the Mui Tsai Experience

Data Set Creation and Statistical Analysis: Testing the effects of Facebook usage in an ethnically polarized setting (data set is here)