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 […]
Text analysis is a quickly growing field focused on analyzing texts (potentially thousands or millions of texts) using code. This workshop will introduce you to Constellate, a text analysis tool that you have access to as a member of U of T. For those new to text analysis, Constellate offers a gentle introduction to using […]
A network is a way of specifying relationships among a collection of entities or actors. Networks come up in a variety of situations; for example, they can describe relationships between characters in literary works, how authors cite each other in a particular discipline or how people interact on social media. Through a combination of lecture […]
In this course students will be instructed in how to program in R. Ultimately students will learn how to use R to analyze, process and visualize data. This course is designed for students with little to no experience in programming. This is a graduate course that can be taken for credit by UofT Biochemistry graduate […]
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 […]
