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X-WR-CALDESC:Events for Office of Advanced Research Computing
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DTSTART;TZID=America/New_York:20240301T130000
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UID:9627-1709298000-1709308800@oarc.rutgers.edu
SUMMARY:Intro to Python
DESCRIPTION:Register to attend this workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. \nPython 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 is one of the reasons why Python is preferable as the language of choice to learn a computer program. \nThis workshop offers practical experience in learning Python\, especially for the beginners. By the end of the workshop\, the participants will be able to write simple scripts\, understand Python modules\, and manage packages. \nObjectives \n\nExplore command line executions vs Jupyter Notebooks\nUnderstand how to use data structures – variables\, lists\, and dictionaries\nConstruct loops for repeated task executions\nCreate functions for reusing code blocks\nUnderstand Python modules\nManage and Install Python packages\n\nAmarel account: Apply here as soon as possible. You must have an Amarel account set up before the workshop. \nVPN setup: You have to be connected on Rutgers’ network or be on VPN to access Amarel resources. \nSSH setup: Windows users must install an SSH client like PuTTY or MobaXterm. Alternatively\, Windows 10 users can install the complete Windows Subsystem for Linux. \nIf you have questions or need help\, please email Bala Desinghu. \nRegister to attend the workshop: \n	Notice: JavaScript is required for this content.
URL:https://oarc.rutgers.edu/event/intro-to-python/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240305T150000
DTEND;TZID=America/New_York:20240305T163000
DTSTAMP:20260416T221505
CREATED:20240119T195047Z
LAST-MODIFIED:20240119T202833Z
UID:9874-1709650800-1709656200@oarc.rutgers.edu
SUMMARY:R for interactivity: an introduction to Shiny
DESCRIPTION: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. \n			\n				Learn more and register
URL:https://oarc.rutgers.edu/event/r-for-interactivity-an-introduction-to-shiny/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240307T160000
DTEND;TZID=America/New_York:20240307T173000
DTSTAMP:20260416T221505
CREATED:20240118T220939Z
LAST-MODIFIED:20240119T131346Z
UID:9790-1709827200-1709832600@oarc.rutgers.edu
SUMMARY:Introduction to machine learning: supervised learning
DESCRIPTION:This workshop is tailored for beginners in machine learning. It focuses on supervised learning algorithms that are a cornerstone of machine learning\, where the algorithm learns from labeled training data\, helping to predict outcomes for unforeseen data. Classification and Regression will be introduced. Participants will learn about key algorithms like Linear Regression and Decision Trees\, exploring how these methods enable machines to learn from and make predictions based on data. \n			\n				Learn more and register
URL:https://oarc.rutgers.edu/event/introduction-to-machine-learning-supervised-learning/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240319T150000
DTEND;TZID=America/New_York:20240319T163000
DTSTAMP:20260416T221505
CREATED:20240119T204100Z
LAST-MODIFIED:20240119T210212Z
UID:9879-1710860400-1710865800@oarc.rutgers.edu
SUMMARY:Data Publication 2 (publishing to data repositories and creating R packages)
DESCRIPTION:Sharing your data and code is the essential step in maximizing the impact and usefulness of your research. \nThis workshop first reviews repositories for data publication such as Dataverse\, ICPSR\, OSF\, Zenodo\, and more. Then we turn to a detailed discussion of building R packages. \nR Packages are an excellent way to distribute collections of data and code. Following on the release of the 2nd edition of Hadley Wickham’s R Packages book\, this workshop reviews the package creation process\, covering prerequisites\, the steps involved in creating a complete package\, and following up on documentation and testing. \n			\n				Learn more and register
URL:https://oarc.rutgers.edu/event/data-publication-2/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240321T160000
DTEND;TZID=America/New_York:20240321T173000
DTSTAMP:20260416T221505
CREATED:20240119T134818Z
LAST-MODIFIED:20240119T135025Z
UID:9806-1711036800-1711042200@oarc.rutgers.edu
SUMMARY:Introduction to machine learning: unsupervised learning
DESCRIPTION:This workshop is designed to introduce the concepts of unsupervised learning\, a branch of machine learning where algorithms infer patterns from unlabelled data. The course covers clustering methods like K-means and DBSCAN\, used to identify inherent groupings in data. It also explores dimensionality reduction techniques such as PCA\, which simplify complex data sets while preserving their key features. Additionally\, the session introduces association rules\, a method for finding interesting relationships within data sets. This workshop is ideal for those interested in learning how to extract insights from data without predetermined labels or categories. \n			\n				Learn more and register
URL:https://oarc.rutgers.edu/event/introduction-to-machine-learning-unsupervised-learning/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240328T160000
DTEND;TZID=America/New_York:20240328T173000
DTSTAMP:20260416T221506
CREATED:20240119T140301Z
LAST-MODIFIED:20240119T140634Z
UID:9815-1711641600-1711647000@oarc.rutgers.edu
SUMMARY:Introduction to deep learning
DESCRIPTION: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 recurrent neural networks (RNNs)\, which are crucial for handling sequential data like text and speech. \n			\n				Learn more and register
URL:https://oarc.rutgers.edu/event/introduction-to-deep-learning/
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