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A valid SUNet ID is needed in order to enroll in a class. University IT Technology Training classes are only available to Stanford University staff, faculty, or students.
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Build custom forms, then collect and analyze response data with filters, formulas, and charts.Format content and manipulate data within files.Create, upload, download, export, and publish documents, spreadsheets, forms, and presentations.Google Drive Apps: Download, install and use Google Drive applications to access, edit, and sync files across devices.Document Collaboration: Learning how to share and collaborate on documents simultaneously with users within and outside of your organization.Presentations and Forms: Building dynamic presentations and forms that can be shared from a local device or computer, published to the web, or embedded in a website.Formatting and Formulas: Learning basic and advanced tricks to format content within documents and analyze data using formulas within spreadsheets.Intro to Google Docs Files: Creating, uploading, and organizing folders, documents, spreadsheets, presentations, and forms. Are you looking for a live training session to help you smoothly and confidently transition to Google Drive as a replacement for Stanford University Box You're invited to join a 1.5-hour Zoom webinar training session taught by the University IT Tech Training team, offered at no cost to you.The Stanford Drive-In has been in continuous operation since 1952. 21,304 likes 895 talking about this 6,823 were here. Our Big Boss had hired a car and took 7 of us to. Learn to create and manage Google Docs, and best practices for managing cloud-based files including publishing, sharing, and changing file permissions. The Stanford Drive-In has been in continuous operation. During my recent visit to San Jose, we planned to go to Stanford University and the famous Google Office.
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Students will work with large datasets of their choosing.Become more comfortable with the features and functionality of Google Docs & Drive. Computational lab course that spans research data processing workflow starting just after the point of acquisition through to computation and visualization.
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