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Events for October 4 – February 7 – Page 3 – Office of Advanced Research Computing Events for October 4 – February 7 – Page 3 – Office of Advanced Research Computing

Mastering data analysis: Pandas and NumPy essentials

This workshop is designed to equip learners with powerful tools for data analysis in Python. Participants will delve into the world of NumPy, exploring its efficient arrays and array operations, which form the backbone of numerical computing in Python. The workshop then shifts to Pandas, where learners will get hands-on experience with its fundamental data … Read More

Love Data Week! Finding, Creating and Working with GIS Data

Location can play an important part in your research. "Everything happens somewhere..." In this short, interactive workshop, we'll learn about spatial data, explore GIS (geographic information systems) data resources and search strategies, review critical data literacy and attribution information, and discuss building spatial datasets.

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. 

Love Data Week! Unveiling Data Stories: Python for Visualization and Exploration

This workshop is designed to guide participants through the process of revealing hidden stories in data using Python. It focuses on using Matplotlib and Seaborn, two prominent visualization tools, for effective exploratory data analysis (EDA). This workshop emphasizes the creation of engaging visual narratives, enabling participants to transform complex data insights into compelling and understandable … Read More

Amarel monthly maintenance

Maintenance is usually scheduled for weekdays because it often involves coordination with university facilities teams or external vendors. There may also be times when Amarel must be unavailable due to externally-scheduled data center facilities, power, or telecommunications maintenance. When this happens, we will do our best to avoid adding to a month’s downtime with our … Read More

ArcGIS StoryMaps, WebApps and Dashboards

Most people can relate to and understand "where" when sharing information. In this short, interactive workshop, we will explore telling the story of your research using StoryMaps or another of the web applications that integrate work done in ArcGIS Online. Previous knowledge of geographic information systems (GIS) is not required. Make sure to register for … Read More

R data wrangling with dplyr, tidyr, readr, and more

This workshop offers an introduction to the fundamentals of deep learning, a highly influential branch of artificial intelligence. This session focuses on the core concepts of neural networks, including feedforward neural networks, the simplest type of artificial neural network architecture. The course also covers convolutional neural networks (CNNs), essential for image and video recognition, and … Read More

Mathematical foundations for data science

This workshop offers a brief yet comprehensive overview of essential mathematics for data science. It covers foundational statistics and probability, crucial for model understanding, and basic hypothesis testing techniques. It also introduces linear algebra concepts like vectors and matrices, alongside fundamental calculus for derivatives and integrals.

Intro to Python

Register to attend this workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. Python is a popular language in academia and industry for developing software and data science applications. Compared to the other generic programming languages like C, C++, or Java, learning Python is relatively easy. This … Read More

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.