In about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.Format: online only
In-Person Location: Robarts Library, 5th Floor, Room 5-053 (directly across from the elevator). Map & Data Library Computer Lab Excel is a popular spreadsheet software that allows you to organize, modify and analyse your data. In this 2 hour hands-on workshop, you will gain a deeper understanding of the uses and types of data that […]
Do you want to develop your R skills to advance your data science skills? R is a popular open-source statistical programming language that is popular in academia and industry. This workshop gently introduces users to intermediate level tools in R including the dplyr package for data manipulation, if statements, for loops, functions and the ggplot2 […]
This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in […]
In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large […]
Are you interested in sharing your data with other researchers? Has a journal or funder asked you to share your data? Would you like to house your research team’s data in one place? In this session, participants will learn how to organize and publish research data in the University of Toronto Dataverse, U of T’s […]
The Canadian Hub for Health Intelligence and Innovation in Infectious Diseases (HI3), led by the University of Toronto, is a newly awarded collaborative, multi-disciplinary and multi-sector coalition of more than 80 partners with a goal to support a robust domestic pipeline of life-saving vaccines and therapeutics targeting existing and emerging infectious threats. HI3 will be […]
The Anti-Racism & Cultural Diversity Office (ARCDO) and the University of Toronto is committed to supporting faculty, staff and students in the tri-campus community and responding to the needs of campus communities experiencing racism and religious discrimination through diverse programming and resources. We are aware of the complexities and nuances in discussions surrounding faith, discrimination […]
In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large […]
This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in […]
