Managing research data is a key component of any research project, and - when done right - can save you time and effort. In this session, participants will learn about current requirements and best practices for managing research data at all stages of a research project. Topics covered include: Journal and funder requirements Data management […]
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 […]
Canada is a leader in innovation, research and development, thanks to the research community’s commitment to open science and international collaboration. However, this strength also makes Canadian research an attractive target for malicious actors. The transfer of our cutting-edge research can result in: Damage to the integrity of Canadian academic and research institutions Advancements in […]
Join us for the third workshop in the CRIS series Drawing Across the Disciplines. (https://cris.utoronto.ca/related/drawing-across-the-disciplines/)This session focuses on Graphic Facilitation. This 3-hour hands on workshop is a follow-on session from the January 18th panel discussion on Graphic Facilitation which is the technique of drawing images and words to capture complex ideas and concepts in a […]
An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for […]
Learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP execution and memory model, performance, reductions and load balancing.Format: Virtual
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 […]
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 and functions. It is […]
