Research computing

Further research computing courses

Courses tagged with "Research computing"

This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.

Format: Virtual

Date: Mon, 27 May 2024 - 1:00 pm
Scientific Computing Credits: 3

Working with Advanced Research Computing and High Performance Computing systems involves using the Linux command line. This workshop will cover Linux commands to improve your productivity on the command line. 
Format: In person, but also broadcast and recorded.

Date: Mon, 12 Dec 2022 - 1:00 pm
Scientific Computing Credits: 3
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course).
Start date: 7 Nov 2017
End date: 30 Nov 2017
Learn about research computing even with little programming experience. Covers basics of programming in python, best practices and visualization. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). The course can be taken as a mini/modular graduate course by Physics students. This course can also be taken by PhD students for graduate credits from the Department of Ecology & Evolutionary Biology (EEB) at the UofT. Interested students from the EEB department should contact Prof. Helen Rodd in advance.
Start date: 22 Nov 2016
End date: 15 Dec 2016
Learn about research computing even with little programming experience. Covers basics of programming in python, best practices and visualization. The course will last 4 weeks with 2 lectures per week (mini/modular grad course).
Start date: 3 Nov 2015
End date: 26 Nov 2015

Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.

Note: this event has been moved from April 8th to April 15th.

Format: Virtual

Date: Mon, 15 Apr 2024 - 1:00 pm
Scientific Computing Credits: 3

Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.

Format: Virtual

Date: Mon, 6 Nov 2023 - 1:00 pm
Scientific Computing Credits: 3

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.

Date: Mon, 13 Mar 2023 - 1:00 pm
Scientific Computing Credits: 3

This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.

Format: In-person and On-line (zoom)

Location: SciNet Teaching Room, 11th floor on the MaRS West tower,  661 University Ave., Suite 1140, Toronto, ON M5G 1M1

Time:  1:00 pm - 4:00 pm EST


Date: Mon, 17 Apr 2023 - 1:00 pm
Scientific Computing Credits: 3

Windows Subsystem for Linux (WSL) is Microsoft's implementation of Linux container on Windows. WSL allows users to run various Linux distributions inside Windows and provides fully functional Linux environments for routine tasks. This course explores the usage of WSL and Docker Desktop on Windows. 
Format: In-person

Date: Mon, 13 Feb 2023 - 1:00 pm
Scientific Computing Credits: 3

Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience.

Date: Tue, 12 Apr 2022 - 1:00 pm
Scientific Computing Credits: 3

Working with Advanced Research Computing and High Performance Computing systems involves using the Linux command line. This workshop will cover Linux commands to improve your productivity on the command line.

Date: Tue, 22 Feb 2022 - 1:00 pm
Scientific Computing Credits: 3

Working with Advanced Research Computing and High Performance Computing systems involves using the Linux command line.  This workshop will cover Linux commands to improve your productivity on the command line.

Start date: 21 Jun 2021
End date: 25 Jun 2021

Working with Advanced Research Computing and High Performance Computing systems involves using the Linux command line. This workshop will cover Linux commands to improve your productivity on the command line.

Date: Wed, 17 Nov 2021 - 12:00 am
Scientific Computing Credits: 3
Increase you Linux (bash) command line productivity. Requires some basic Linux command line experience.
Date: Wed, 23 Oct 2019 - 1:00 pm
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course).
Start date: 5 Nov 2019
End date: 5 Dec 2019
Master the Linux command line and its processes; explore filesystems to check directory status and access modification times; create and manage user and group passwords securely. -- Prerequisite: some understanding of Linux CLI, be able to open a terminal, and use simple commands
Teacher: SciNet Team
Date: Mon, 24 Jun 2019 - 10:45 am
This session gives an introduction to Julia, a programming language that was designed from the beginning for high performance. -- Prerequisite: some programming experience in another programming language.
Teacher: SciNet Team
Date: Fri, 28 Jun 2019 - 9:30 am
Scientific Computing Credits: 1
High Performance Computing Credits: 2
Increase you Linux (bash) command line productivity. Requires some basic Linux command line experience.
Teacher: Bruno Mundim
Date: Wed, 10 Apr 2019 - 1:00 pm
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience
Date: Wed, 13 Feb 2019 - 1:00 pm
Learn how to write bash script, use environment variables, how to control process, and much more. Requires some linux basic command line experience.
Teacher: SciNet Team
Date: Wed, 17 Oct 2018 - 1:00 pm
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course).
Start date: 6 Nov 2018
End date: 6 Dec 2018
Part of the 2017 Ontario Summer School.
Teacher: SciNet Team
Date: Tue, 25 Jul 2017 - 9:30 am
Learn how to write bash script, use environment variables, how to control process, and much more. Requires some linux basic command line experience.
Teacher: SciNet Team
Date: Wed, 25 Oct 2017 - 1:00 pm
This workshop is part of the 2017 Chemical BioPhysics Symposium. A basic introduction to the R programming language will be covered. Participants willing to follow along examples presented, should bring a laptop with R or Rstudio installed.
Teacher: Marcelo Ponce
Date: Fri, 5 May 2017 - 10:00 am
Part of the 2016 Ontario Summer School, in this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.
Teacher: SciNet Team
Date: Wed, 13 Jul 2016 - 9:30 am
Part of the 2016 Ontario Summer School, this half-day session offers a brief introduction to R, with a focus on data analysis and statistics.
Teacher: SciNet Team
Date: Tue, 12 Jul 2016 - 9:30 am
Learn how to create Graphical User Interfaces (GUIs) in Python with Tkinter.
Teacher: Erik Spence
Date: Tue, 9 Sep 2014 - 2:00 pm
Scientific Computing Credits: 2
Learn about research computing even with little programming experience. Covers basics of programming in python, best practices and visualization. (mini/modular grad course)
Teacher: SciNet Team
Start date: 4 Nov 2014
End date: 27 Nov 2014
Learn about research computing even with little programming experience. Covers basics of programming in python, best practices and visualization.
Start date: 5 Nov 2013
End date: 28 Nov 2013

An introduction to basic concepts in High-Performance Computing (HPC).  This is intended to be a high-level primer for those largely new to HPC.  Topic will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism and a high-level overview of parallel programming models.

Format: Virtual

Teacher: Bruno Mundim
Start date: 25 Sep 2023
End date: 29 Sep 2023
High Performance Computing Credits: 4

An introduction to basic concepts in High-Performance Computing (HPC).  This is intended to be a high-level primer for those largely new to HPC.  Topic will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism and a high-level overview of parallel programming models.

Teacher: Bruno Mundim
Start date: 21 Mar 2022
End date: 1 Apr 2023
High Performance Computing Credits: 4

An introduction to basic concepts of High-Performance Computing (HPC).  This is intended to be a high-level primer for those largely new to HPC. Topics will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism, and a high level overview of parallel programming models.

Start date: 5 Jul 2021
End date: 9 Jul 2021
High Performance Computing Credits: 4
An introduction to basic concepts of high-performance computing. It is intended to be a high-level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming weeks. Topics will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism, and a high level overview of parallel programming models.
Start date: 9 Jun 2020
End date: 12 Jun 2020
An introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism, and a high level overview of parallel programming models. -- Prerequisites: C, C++ or Fortran programming, experience editing and compiling code in a Linux environment.
Teacher: SciNet Team
Date: Mon, 24 Jun 2019 - 10:45 am
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism, and a high level overview of parallel programming models.
Teacher: Michael Nolta
Date: Mon, 11 Jun 2018 - 9:30 am
Part of the 2017 Ontario Summer School.
Teacher: SciNet Team
Date: Mon, 24 Jul 2017 - 9:00 am
Part of the 2016 Ontario Summer School, this half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.
Teacher: SciNet Team
Date: Mon, 11 Jul 2016 - 9:30 am
This session will provide an introduction to basic concepts of high performance computing. Part of the 2015 Ontario HPC Summer School, central edition
Teacher: SciNet Team
Date: Mon, 13 Jul 2015 - 1:30 pm
Part of the 2014 Ontario Summer School on High Performance Computing
Date: Mon, 9 Jun 2014 - 1:30 pm
Part of the Ontario Summer School on High Performance Computing 2013 -Toronto
Teacher: SciNet Team
Date: Tue, 7 May 2013 - 1:30 pm
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience.
Teacher: SciNet Team
Category: Data Science
Start date: 21 Sep 2020
End date: 25 Sep 2020
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience.
Category: Data Science
Date: Wed, 19 Feb 2020 - 1:00 pm
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization. -- Prerequisite: some programming experience in another programming language.
Category: Data Science
Date: Tue, 25 Jun 2019 - 9:30 am
Data Science Credits: 3
This half-day session offers a brief introduction to R, with a focus on data analysis and statistics. We will discuss and introduce the following topics: the R interface, primitive data types, lists, vectors, matrices, and data frames - a crucial data type in data analysis and a trademark in the R language. Advanced topics to be covered include: basics statistics and function creation; *apply family functions; and basics of scripting. Time depending we may cover and discuss some data management strategies (ie. saving results, workspaces and installing packages) and basic plotting. -- Prerequisite: some programming experience in another programming language.
Teacher: SciNet Team
Category: Data Science
Date: Mon, 24 Jun 2019 - 1:30 pm
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.
Teacher: Michael Nolta
Category: Data Science
Date: Tue, 12 Jun 2018 - 1:30 pm
This half-day session offers a brief introduction to R, with a focus on data analysis and statistics. We will discuss and introduce the following topics: the R interface, primitive data types, lists, vectors, matrices, and data frames - a crucial data type in data analysis and a trademark in the R language. Advanced topics to be covered include: basics statistics and function creation; *apply family functions; and basics of scripting. Time depending we may cover and discuss some data management strategies (ie. saving results, workspaces and installing packages) and basic plotting.
Teacher: Marcelo Ponce
Category: Data Science
Date: Tue, 12 Jun 2018 - 9:30 am
Part of the 2017 Ontario Summer School.
Teacher: SciNet Team
Category: Data Science
Date: Tue, 25 Jul 2017 - 1:30 pm
Part of the 2015 Ontario HPC Summer School. This session covers how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.
Teacher: SciNet Team
Category: Data Science
Date: Tue, 14 Jul 2015 - 9:30 am
This session offers a brief introduction to R, with a focus on data analysis and statistics. Part of the 2015 Ontario HPC Summer School.
Teacher: SciNet Team
Category: Data Science
Date: Mon, 13 Jul 2015 - 9:30 am