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X-WR-CALDESC:Events for Workshops @ UCLA
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261105T100000
DTEND;TZID=America/Los_Angeles:20261105T110000
DTSTAMP:20260921T183014Z
CREATED:20260921T183014Z
LAST-MODIFIED:20260921T183014Z
UID:10003823-1793872800-1793876400@workshops.ucla.edu
SUMMARY:Introduction to Document Accessibility (Google docs\, Word\, PDF)
DESCRIPTION:This session provides an introduction to creating accessible documents in Google Docs\, Microsoft Word\, and PDFs. Participants will learn the fundamentals of digital accessibility\, including how to use proper heading structure\, write effective alt-text for images\, create descriptive links\, and ensure sufficient color contrast. The training will also demonstrate how to use built-in and automated accessibility checkers to identify and correct common issues.
URL:https://workshops.ucla.edu/workshop/introduction-to-document-accessibility-google-docs-word-pdf-7/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261105T100000
DTEND;TZID=America/Los_Angeles:20261105T120000
DTSTAMP:20260921T183014Z
CREATED:20260921T183014Z
LAST-MODIFIED:20260921T183014Z
UID:10003824-1793872800-1793880000@workshops.ucla.edu
SUMMARY:Interactive Computing on the Hoffman2 Cluster
DESCRIPTION:This hands-on session covers everything you need to work interactively on the Hoffman2 Cluster: navigating the filesystem\, loading software with Environment Modules\, and requesting compute resources through the job scheduler to launch TUI and GUI applications. We’ll then apply those same skills to a widely used case — running Jupyter Notebook or JupyterLab on the cluster\, tunneling in securely\, and working in Python/conda\, R\, Julia\, or another language of your choice. Ideal for researchers who want to explore tools\, test code\, or prototype analyses in real time.
URL:https://workshops.ucla.edu/workshop/interactive-computing-on-the-hoffman2-cluster/
LOCATION:OARC Portal\, Math Sciences 5628\, 5628 Math Science Building\, UCLA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261105T130000
DTEND;TZID=America/Los_Angeles:20261105T150000
DTSTAMP:20260921T183015Z
CREATED:20260921T183015Z
LAST-MODIFIED:20260921T183015Z
UID:10003825-1793883600-1793890800@workshops.ucla.edu
SUMMARY:Data Visualization with Python II: Making Interactive Plots and Dashboards
DESCRIPTION:A static figure answers the question you chose in advance\, while an interactive one lets readers explore the data and ask their own: zooming into a region\, filtering to a subgroup\, or hovering to see underlying values. The second part of this series moves from static graphics to interactive visualization\, introducing common Python libraries for the task: Plotly and Altair for building interactive charts\, and Streamlit for assembling those charts into dashboards that others can use. We’ll also briefly survey where these tools reach their limits and what to use instead: Dash for production dashboards that need more control over layout and callbacks\, and the HoloViews\, Panel\, and Datashader ecosystem for datasets too large to render point by point. Finally\, we’ll touch on how to share the results\, from self-contained HTML files that need no server to applications deployed on shared infrastructure. We will go through several interactive exercises so that attendees can gain direct experience in using these libraries and will be prepared to learn more on their own after the workshop. Part I is useful background but not required; basic familiarity with Python and Pandas will be useful.
URL:https://workshops.ucla.edu/workshop/data-visualization-with-python-ii-making-interactive-plots-and-dashboards-4/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261109T130000
DTEND;TZID=America/Los_Angeles:20261109T160000
DTSTAMP:20260921T183027Z
CREATED:20260921T183027Z
LAST-MODIFIED:20260921T183027Z
UID:10003826-1794229200-1794240000@workshops.ucla.edu
SUMMARY:Introduction to directed acyclic graphs (DAGs) for causal inference in R
DESCRIPTION:Directed Acyclic Graphs (DAGs) have emerged as an important tool in causal modeling to understand the relationships among variables. DAGs can inform what variables should be included or excluded in a statistical model intended to minimize bias in the estimation of a causal effect. This workshop discusses the basics of DAGs used for causal inference and outlines simple rules one can follow to know which variables to include in a causal statistical model. The R package daggity will be discussed to visualize DAGs.
URL:https://workshops.ucla.edu/workshop/introduction-to-directed-acyclic-graphs-dags-for-causal-inference-in-r-2/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261112T100000
DTEND;TZID=America/Los_Angeles:20261112T120000
DTSTAMP:20260921T183624Z
CREATED:20260921T183028Z
LAST-MODIFIED:20260921T183624Z
UID:10003828-1794477600-1794484800@workshops.ucla.edu
SUMMARY:Batch Job Submission with Slurm & Optimizing and Managing Your Workflows on the Hoffman2 Cluster
DESCRIPTION:Batch computing is how you turn a single analysis into hundreds or thousands\, scaling your research well beyond what you could run by hand. This workshop covers writing and submitting batch scripts\, requesting the CPU and GPU resources your jobs need\, monitoring job status\, and managing output — the core skillset for running larger or automated workloads on the Hoffman2 Cluster. Because job scripts are one of the areas most affected by the cluster’s move to a new scheduler\, we’ll spend dedicated time on what needs to change to take a script from Grid Engine to Slurm.
URL:https://workshops.ucla.edu/workshop/batch-job-submission-on-the-hoffman2-cluster/
LOCATION:OARC Portal\, Math Sciences 5628\, 5628 Math Science Building\, UCLA
CATEGORIES:Training workshop / Tutorial
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261112T110000
DTEND;TZID=America/Los_Angeles:20261112T120000
DTSTAMP:20260921T183027Z
CREATED:20260921T183027Z
LAST-MODIFIED:20260921T183027Z
UID:10003827-1794481200-1794484800@workshops.ucla.edu
SUMMARY:Introduction to Video\, Audio\, and Youtube Accessibility
DESCRIPTION:In this session participants will learn about video and audio accessibility best practices. \nBy the end of this training you should be able to:\n-Create an WCAG 2.1 AA caption file\n-Identify closed and open captions\n-Test the player controls of an embedded video\n-Add an audio description to a Youtube video\n-Create an accessible transcript
URL:https://workshops.ucla.edu/workshop/introduction-to-video-audio-and-youtube-accessibility/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261113T110000
DTEND;TZID=America/Los_Angeles:20261113T120000
DTSTAMP:20260921T183028Z
CREATED:20260921T183028Z
LAST-MODIFIED:20260921T183028Z
UID:10003829-1794567600-1794571200@workshops.ucla.edu
SUMMARY:A Satellite Analysis Reveals Why Structures Burn While Neighbors Survive Disaster
DESCRIPTION:In this workshop you will learn how to develop image processing workflows in AWS using generative AI services.
URL:https://workshops.ucla.edu/workshop/a-satellite-analysis-reveals-why-structures-burn-while-neighbors-survive-disaster/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261116T130000
DTEND;TZID=America/Los_Angeles:20261116T160000
DTSTAMP:20260921T183029Z
CREATED:20260921T183029Z
LAST-MODIFIED:20260921T183029Z
UID:10003830-1794834000-1794844800@workshops.ucla.edu
SUMMARY:Generalized Linear Regression Models in R
DESCRIPTION:This workshop introduces the generalized linear regression model\, which extends the linear regression model to accommodate outcomes with different distributions. The workshop briefly reviews linear regression concepts as necessary\, and then discusses logistic regression for binary outcomes and Poisson and negative binomial models for count outcomes. Examples of running each of these models in R are provided. Some exposure to both linear regression and R would be helpful but are not required.
URL:https://workshops.ucla.edu/workshop/generalized-linear-regression-models-in-r-2/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261119T100000
DTEND;TZID=America/Los_Angeles:20261119T120000
DTSTAMP:20260921T183030Z
CREATED:20260921T183030Z
LAST-MODIFIED:20260921T183030Z
UID:10003832-1795082400-1795089600@workshops.ucla.edu
SUMMARY:Computing on the National Research Platform
DESCRIPTION:The National Research Platform (NRP) gives researchers access to a distributed\, Kubernetes-based cyberinfrastructure spanning dozens of institutions\, including a large pool of GPUs and high-throughput storage. For researchers coming from traditional HPC batch schedulers\, the model can be unfamiliar: the unit of work is a containerized workload rather than a script submitted to a queue. \nIn this interactive workshop\, participants will learn how to run tasks on the platform. We start with the conceptual model — namespaces\, Pods\, containers\, and how scheduling differs from a queue — then move directly to practice. Participants will launch an interactive Pod for development\, submit a batch Job\, and request a specific GPU type\, learning how resource requests and limits affect placement. We cover attaching a persistent volume so results survive the Pod\, and close with reading logs\, diagnosing common failure modes\, and norms for sharing a multi-institution resource. \nPrerequisites: participants should arrive with NRP account access and kubectl already installed. Setup instructions will be circulated in advance\, and help will be available before the start. Users unfamiliar with containerization are recommended to attend the “Containerization for Reproducible Scientific Computing” workshop.
URL:https://workshops.ucla.edu/workshop/computing-on-the-national-research-platform/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261119T110000
DTEND;TZID=America/Los_Angeles:20261119T120000
DTSTAMP:20260921T183029Z
CREATED:20260921T183029Z
LAST-MODIFIED:20260921T183029Z
UID:10003831-1795086000-1795089600@workshops.ucla.edu
SUMMARY:Introduction to Digital Accessibility Testing
DESCRIPTION:Audience: UCLA web editors\, content creators\, IT staff\, and program managers Tools Covered: WAVE Chrome plug-in\, Siteimprove Accessibility\, manual keyboard testing \nBy the end of this training\, participants will:\n-Understand the basics of digital accessibility and UCLA’s WCAG 2.1 AA compliance requirements\n-Learn how to use WAVE for page-by-page testing\n-Learn how to use Siteimprove for whole-site accessibility scanning and monitoring\n-Practice manual testing with tab navigation to identify barriers that automated tools miss.\n-Know how to prioritize and remediate common accessibility issues
URL:https://workshops.ucla.edu/workshop/introduction-to-digital-accessibility-testing-9/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261211T110000
DTEND;TZID=America/Los_Angeles:20261211T123000
DTSTAMP:20260921T183030Z
CREATED:20260921T183030Z
LAST-MODIFIED:20260921T183030Z
UID:10003833-1796986800-1796992200@workshops.ucla.edu
SUMMARY:Learn prompt engineering and Retrieval Augmented Generation using LLMs
DESCRIPTION:In this workshop you will how to use LLMs and RAG in concert with prompt engineering to build purpose-driven AI productivity tools
URL:https://workshops.ucla.edu/workshop/learn-prompt-engineering-and-retrieval-augmented-generation-using-llms/
LOCATION:Zoom
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