Presenters: Kirsta Stapelfeldt, Head, Digital Scholarship Unit, UTSC; Paulina Rousseau, Liaison Librarian, UTSC; William Heikoop, Coordinator, Digital Learning Innovation, UofT Open Repositories are closely associated with providing free access to research outputs and results for anyone to make use of. They can go beyond research outputs and can also contain materials that support curriculum and […]
Instructor: Stephanie Quail, Scholarly Communications Librarian, York University In 2020, two librarians from York University created an open educational resources (OER) mini-course for faculty who received funding from York's internal teaching and learning grant. While the program was initially conceived as an in-person learning opportunity, the shift to online learning during Covid-19 required that the […]
Instructors: Monica Shah, Associate, Digital Transformation, eCampusOntario; Laura Viselli, Senior Manager, Research and Foresight, eCampusOntario Target Audience: This Digital Transformation (Dx) Leadership program is intended for individuals in a leadership role, Deans, Administrators, faculty, instructors, and anyone who aspires to take a leadership role. Description of the webinar: This webcast will feature eCampusOntario’s newly […]
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 how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience.Format: In-person, but will also be broadcast and recorded.
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 […]
