Intro to SciNet, Niagara and Mist
661 University Ave., Toronto, M5G 1M1, CanadaA quick introduction how to use SciNet and the Niagara and Mist supercomputers. Location: SciNet Online -- Powered by icalfilter.com --
A quick introduction how to use SciNet and the Niagara and Mist supercomputers. Location: SciNet Online -- Powered by icalfilter.com --
This open drop-in session is intended for SharePoint site owners and administrators who have questions, want to learn about a particular feature or need some assistance with content in the Virtual Bootcamp. We recommend that all new site owners or administrators begin with the SharePoint Site Admin Virtual Bootcamp and then drop-in for more support […]
In this course data analysis techniques utilizing the R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing. The goal of this course is to prepare graduate students to perform scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into […]
Researchers are more frequently undertaking mixed methods projects, which allow them to take advantage of the strengths of both qualitative and quantitative data. NVivo will help you organize and analyze the qualitative data, as well as use quantitative data to parse and ask questions of your qualitative data. In NVivo you will be able to […]
Researchers are more frequently undertaking mixed methods projects, which allow them to take advantage of the strengths of both qualitative and quantitative data. NVivo will help you organize and analyze the qualitative data, as well as use quantitative data to parse and ask questions of your qualitative data. In NVivo you will be able to […]
Researchers are more frequently undertaking mixed methods projects, which allow them to take advantage of the strengths of both qualitative and quantitative data. NVivo will help you organize and analyze the qualitative data, as well as use quantitative data to parse and ask questions of your qualitative data. In NVivo you will be able to […]
The Toronto Data Workshop (TDW) is a weekly hour-long discussion where industry and academic participants collectively consider, collate, share, and disseminate best practices in the critical initialdata-centric steps of any data science project. The organising committee - Faria Khandaker, Kelly Lyons, and Rohan Alexander – would like to invite you to the TDW Fall term. […]
The Research & Innovation Dashboards (https://utoronto.sharepoint.com/sites/ResearchInnovationDashboards) enable self-service data analysis for data-informed decision making, and the Functional User Group - our FUG - is at the heart of this dashboards project! Join us at this session for an update on the project and a demo of what's in the hopper.
We are pleased to offer this information session to the U of T researchcommunity applying to the Fall 2020 NSERC Discovery Grant program This session will also include guest speaker, Professor Christopher Yip, who will outline details in the application and evaluation process. Topics will include program's application requirements, eligibility, changes for this year’s competitions, evaluation criteria and […]
Have questions about the UTSC Library? We’ve got answers! Drop in for a Q&A session at the online library help desk with the UTSC Library User Services team. After taking this session, participants will be able to: find and navigate the library booking system, e-reserves access library research tools Contact liaison librarians tools Locate information […]
Talk title: Beyond sample-splitting: valid inference while “double-dipping” Dr. Daniela Witten Professor of Statistics and Biostatistics Dorothy Gilford Endowed Chair University of Washington Free Event | Registration Required: https://www.eventbrite.com/e/data-science-applied-research-and-education-seminar-daniela-witten-tickets-119647409623 Abstract: As datasets continue to grow in size, in many settings the focus of data collection has shifted away from testing pre-specified hypotheses, and towards hypothesis generation. […]