Learn how to apply a complete data analysis pipeline focusing on the key topics: Data loading and cleaning (Pandas) Exploratory data analysis (EDA) Identifying patterns and insights Attendees will develop a clean dataset, EDA notebook, and key insight summary. (Applied Data Science, Workshop 1) Instructor: Terri-Ann Grant Related LibGuide: Data Science - Graduate Specialists by Ryan […]
Events
Events
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The seminar explores the fast-growing interface between mathematical reasoning, formal methods, and modern AI systems. It is co-organized by DIMACS and the Mathematics Department at Rutgers University, New Brunswick. Here is the YouTube channel for the talks in this seminar. Date: Sep 16, 2026 Speaker: Steven Creech (Rutgers) Title/Materials: Euclidean Geometry, AI, and Teaching Time: […]
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This workshop reviews statistical tests, regression, sampling and bootstrap methods, and more. The focus here is on implementing statistics using R, with a comparison to Python techniques for accomplishing similar tasks. Part of the Data Topics series of workshops. Workshop conducted via Zoom. Register to receive the Zoom link with instructions on how to connect. […] |
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Get started early with keeping track of what you read! 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 bibliographies. Bring your personal laptop, download Zotero 9.0 10 for your […]
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This short course helps everyone make those first few steps toward productively using a Linux cluster for research — all members of the Rutgers community have free access to the Amarel Cluster. The workshop covers the basics of HPC Cluster, Web access to the cluster, SLURM, File System and Storage, and Setting up environment for […] |
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NVivo is a qualitative data analysis software that helps researchers manage, code, and markup data for qualitative studies. In this session, participants will get the conceptual background before touching the software, then bring data into NVivo and prepare it for analysis. Memos and mind maps give participants a low-pressure way to start thinking about their […] |
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Coding doesn’t have to be intimidating. Python is one of the easiest programming languages to learn, and it’s used everywhere, from apps to automation to data analysis. In this workshop, we’ll start with the basics, step by step, and show you how Python can be applied to everyday problems in a way that’s simple and […] |
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Learn the foundations of spatial data through these key topics: Spatial data types (points, lines, polygons) Basic mapping Attendees will develop a simple spatial dataset and map visualization. (GIS & Spatial Analytics, Workshop 1) Instructor: Terri-Ann Grant Related LibGuide: Data Science - Graduate Specialists by Ryan Womack Date:Tuesday, September 22, 2026 Time:4:00pm - 6:00pm Time Zone:Eastern […] |
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Schedule subject to change; check https://ai-math-seminar.github.io/seminar/ for speakers, abstracts, and slides. The seminar explores the fast-growing interface between mathematical reasoning, formal methods, and modern AI systems. It is co-organized by DIMACS and the Mathematics Department at Rutgers University, New Brunswick. Here is the YouTube channel for the talks in this seminar. Date: Sep 23, 2026 […]
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This workshop covers basic data visualization in R, with emphasis on ggplot2 and associated packages. The focus here is on R techniques, with a brief comparison to Python techniques for accomplishing similar tasks, such as seaborn and matplotlib. Part of the Data Topics series of workshops. Workshop conducted via Zoom. Register to receive the Zoom […] |
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Please use this link to submit abstracts and/or to register. The Rutgers Postdoctoral Association invites the Rutgers community to attend the 2026 Rutgers University Postdoctoral Research Symposium. Friday September 25 from 9:30am-3:45pm in Kessler Teaching Wing of RWJMS Research Tower (675 Hoes Lane West, Piscataway, NJ). The event will feature interdisciplinary research presentations, networking opportunities with Rutgers […]
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NVivo is a qualitative data analysis software that helps researchers manage, code, and markup data for qualitative studies. In this session, participants will get the conceptual background before touching the software, then bring data into NVivo and prepare it for analysis. Memos and mind maps give participants a low-pressure way to start thinking about their […] |
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Once you’ve taken your first steps with Python, it’s time to do more. In this workshop, we’ll go further into how Python can help you work with information. You’ll learn how to handle collections of data, write simple reusable code, and explore how to pull meaning out of datasets. By working hands-on with examples, you’ll […] |
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Learn to interpret models for decision making through these key topics: Linear and logistic regression Model interpretation (coefficients, significance) Translating results into real-world meaning Attendees will develop a regression model with associated plain-language interpretation. (Applied Data Science, Workshop 2) Instructor: Terri-Ann Grant Related LibGuide: Data Science - Graduate Specialists by Ryan Womack Date:Tuesday, September 29, 2026 […] |
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Schedule subject to change; check https://ai-math-seminar.github.io/seminar/ for speakers, abstracts, and slides. The seminar explores the fast-growing interface between mathematical reasoning, formal methods, and modern AI systems. It is co-organized by DIMACS and the Mathematics Department at Rutgers University, New Brunswick. Here is the YouTube channel for the talks in this seminar. Date: Sep 30, 2026 […]
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Data Visualization 2 This workshop will cover creating interactive visualizations with Shiny in RStudio, as well as delivering Shiny visualizations on the web and hosting a Shiny server. Workshop conducted via Zoom. Register to receive the Zoom link with instructions on how to connect. Supplemental materials are available at https://libguides.rutgers.edu/data_topics Instructor: Ryan Womack Related LibGuide: Data […] |
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