Events

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October,2022
31 Oct 2:00 pm 3:00 pm

Intro to Programming Session

New to programming? Learn the basics of programming using python in eight one-hour sessions over the course of four weeks. Sessions will consist of a mix of lectures and hands-on exercises.Format: In-person. Sessions will be recorded. SciNet Teaching Room
SCMP142 - Oct 2022Show in Google map
November,2022
1 Nov 9:00 am 10:30 am

MSC1090: Lecture 15

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
GB244
MSC1090 - Fall 2022Show in Google map
3 Nov 10:20 am 11:50 am

MSC1090: Lecture 16

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
BL205
MSC1090 - Fall 2022Show in Google map
4 Nov 12:00 pm

Python Programming Exit Test opens

New to programming? Learn the basics of programming using python in eight one-hour sessions over the course of four weeks. Sessions will consist of a mix of lectures and hands-on exercises.Format: In-person. Sessions will be recorded.
SCMP142 - Oct 2022
4 Nov 1:02 pm

Python Programming Exit Test closes

New to programming? Learn the basics of programming using python in eight one-hour sessions over the course of four weeks. Sessions will consist of a mix of lectures and hands-on exercises.Format: In-person. Sessions will be recorded.
SCMP142 - Oct 2022
8 Nov 9:00 am 10:30 am

MSC1090: Lecture 17

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
GB244
MSC1090 - Fall 2022Show in Google map
9 Nov 10:00 am 11:30 am

Intro to SciNet, Niagara and Mist

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 Zoom Meeting SciNet Teaching Room
HPC105 - Nov 2022Show in Google map
10 Nov 10:20 am 11:50 am

MSC1090: Lecture 18

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
BL205
MSC1090 - Fall 2022Show in Google map
15 Nov 9:00 am 10:30 am

MSC1090: Lecture 19

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
GB244
MSC1090 - Fall 2022Show in Google map
17 Nov 10:20 am 11:50 am

MSC1090: Lecture 20

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
BL205
MSC1090 - Fall 2022Show in Google map
21 Nov 12:30 pm 2:00 pm

Parallel Programming with MPI: Session #1

Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems. Format: Online (Zoom) Online
HPC123 - Nov 2022Show in Google map
21 Nov 1:00 pm 4:00 pm

Intro to GIT Version Control

Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration.  In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.Format: In-person, but also will be broadcast and recorded. SciNet Teaching Room
DAT161 - Nov 2022Show in Google map
22 Nov 9:00 am 10:30 am

MSC1090: Lecture 21

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
GB244
MSC1090 - Fall 2022Show in Google map
23 Nov 12:30 pm 2:00 pm

Parallel Programming with MPI - Session #2

Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems. Format: Online (Zoom) Online
HPC123 - Nov 2022Show in Google map
24 Nov 10:20 am 11:50 am

MSC1090: Lecture 22

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
BL205
MSC1090 - Fall 2022Show in Google map
25 Nov 12:30 pm 2:00 pm

Parallel Programming with MPI - Session #3

Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems. Format: Online (Zoom) Online
HPC123 - Nov 2022Show in Google map
28 Nov 1:00 pm 4:00 pm

File Management - Packing Small Files

Managing large amounts of data can be a challenging task. Processing large numbers of files incur heavy overhead of IO communications. This course explores several options such as using Apptainer Overlay and SQLite to pack and reduce a large number of files to few files, and hence, improving IO performance. Python scripts are used throughout the course.Format: On-line (Zoom). Online
DAT171 - Nov 2022Show in Google map
29 Nov 9:00 am 10:30 am

MSC1090: Lecture 23

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
GB244
MSC1090 - Fall 2022Show in Google map
December,2022
1 Dec 10:20 am 11:50 am

MSC1090: Lecture 24

The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language.  Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data.  Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn.  This course is part of the IMS graduate program.
BL205
MSC1090 - Fall 2022Show in Google map
12 Dec 1:00 pm 4:00 pm

Advanced Linux Command Line I

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. SciNet Teaching Room
SCMP271 - Dec 2022Show in Google map
14 Dec 10:00 am 11:30 am

Intro to SciNet, Niagara and Mist

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: In-person as well as broadcast and recorded. SciNet Teaching Room
HPC105 - Dec 2022Show in Google map
January,2023
10 Jan 10:30 am 12:00 pm

EES1137 Lecture 1

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 and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data.  Topics include: Python and R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program must enrol through Acorn/ROSI.
EES1137 - Winter 2023
10 Jan 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1610)

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 one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
11 Jan 10:00 am 11:30 am

Intro to SciNet, Niagara and Mist

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: In-person as well as broadcast and recorded. SciNet Teaching Room
HPC105 - Jan 2023Show in Google map
11 Jan 12:00 pm 1:00 pm

CO Colloquium by Mark Hahn on "Performance: current and upcoming systems"

This week's colloquium: "Performance: current and upcoming systems" by Mark Hahn from SHARCNET. The Compute Ontario Colloquia are weekly Zoom presentations on Advanced Research Computing, High Performance Computing, Research Data Management, and Research Software topics, delivered by staff from three Compute Ontario consortia (CAC, SciNet, SHARCNET) and guest speakers.  The colloquia are one hour long and include time for questions. No enrollment or registration is required. Most presentations are recorded and uploaded to the hosting consortium video channel. Virtual
COCO - 11 Jan 2023Show in Google map
12 Jan 11:00 am 12:30 pm

EES1137 Lecture 2

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 and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data.  Topics include: Python and R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program must enrol through Acorn/ROSI.
EES1137 - Winter 2023
12 Jan 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1510)

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 one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
16 Jan 1:00 pm 4:00 pm

Intro to the Linux Command Line

Working with many of the HPC systems (like those at SciNet) involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this coursse which will cover basic commands. It could be a great boon for your productivity.Format: In person, but also broadcast and recorded. SciNet Teaching Room
SCMP101 - Jan 2023Show in Google map
17 Jan 10:30 am 12:00 pm

EES1137 Lecture 3

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 and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data.  Topics include: Python and R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program must enrol through Acorn/ROSI.
EES1137 - Winter 2023
17 Jan 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1610)

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 one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023