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| November,2022 | |
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3 Nov 10:20 am 11:50 amMSC1090: Lecture 16The 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 2022 |
4 Nov 12:00 pmPython Programming Exit Test opensNew 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 pmPython Programming Exit Test closesNew 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 amMSC1090: Lecture 17The 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 2022 |
9 Nov 10:00 am 11:30 amIntro to SciNet, Niagara and MistIn 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 2022 |
10 Nov 10:20 am 11:50 amMSC1090: Lecture 18The 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 2022 |
15 Nov 9:00 am 10:30 amMSC1090: Lecture 19The 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 2022 |
17 Nov 10:20 am 11:50 amMSC1090: Lecture 20The 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 2022 |
21 Nov 12:30 pm 2:00 pmParallel Programming with MPI: Session #1Learn 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 2022 |
21 Nov 1:00 pm 4:00 pmIntro to GIT Version ControlUsing 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 2022 |
22 Nov 9:00 am 10:30 amMSC1090: Lecture 21The 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 2022 |
23 Nov 12:30 pm 2:00 pmParallel Programming with MPI - Session #2Learn 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 2022 |
24 Nov 10:20 am 11:50 amMSC1090: Lecture 22The 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 2022 |
25 Nov 12:30 pm 2:00 pmParallel Programming with MPI - Session #3Learn 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 2022 |
28 Nov 1:00 pm 4:00 pmFile Management - Packing Small FilesManaging 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 2022 |
29 Nov 9:00 am 10:30 amMSC1090: Lecture 23The 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 2022 |
| December,2022 | |
1 Dec 10:20 am 11:50 amMSC1090: Lecture 24The 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 2022 |
12 Dec 1:00 pm 4:00 pmAdvanced Linux Command Line IWorking 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 2022 |
14 Dec 10:00 am 11:30 amIntro to SciNet, Niagara and MistIn 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 2022 |
| January,2023 | |
10 Jan 10:30 am 12:00 pmEES1137 Lecture 1In 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 pmScientific 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 amIntro to SciNet, Niagara and MistIn 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 2023 |
11 Jan 12:00 pm 1:00 pmCO 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 2023 |
12 Jan 11:00 am 12:00 pmScientific 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 |
12 Jan 11:00 am 12:30 pmEES1137 Lecture 2In 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 |
16 Jan 1:00 pm 4:00 pmIntro to the Linux Command LineWorking 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 2023 |
17 Jan 10:30 am 12:00 pmEES1137 Lecture 3In 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 pmScientific 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 |
18 Jan 12:00 pm 1:00 pmCO Colloquium by Erik Spence on "A comparison of neural network frameworks"This week's colloquium: "A comparison of neural network frameworks" by Erik Spence from SciNet.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 registration is required. Most presentations are recorded and uploaded to the hosting consortium video channel. Virtual | COCO - 18 Jan 2023 |
19 Jan 11:00 am 12:30 pmEES1137 Lecture 4In 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 |
19 Jan 11:00 am 12:00 pmScientific 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 |
23 Jan 12:30 pm 2:00 pmPython to C++ #1C++ is a high level programming language that is extremely useful for scientific applications. The language has historically had a bad reputation, but modern C++ is much improved so that your code can be relatively short and elegant. In this workshop we will teach the basics of C++ for people who are familiar with the basics of programming, and we will especially compare and contrast C++ with Python (only the material covered in SCMP142 "Intro to Programming with Python" is required). Knowing multiple programming languages may be a useful skill: while Python is a wonderful programming language, execution speed is often a practical issue for pure Python applications. For applications where this is an issue, coding in C++ can significantly improve performance. As C++ can relatively easily be integrated in a Python project, it is also possible (and common) to code just the bottleneck in that language.Format: In-person, but also will be broadcast and recorded. SciNet Training Room | SCMP241 - Jan 2023 |
24 Jan 10:30 am 12:00 pmEES1137 Lecture 5In 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 |
24 Jan 11:00 am 12:00 pmScientific 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 |
25 Jan 12:00 pm 1:00 pmCO Colloquium by Jeff Moon on "How Research Data Management (RDM) Intersects with ARC and Why Should I Care?"This week's colloquium: "How Research Data Management (RDM) Intersects with ARC and Why Should I Care?" by Jeff Moon from Compute Ontario.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 registration is required. Most presentations are recorded and uploaded to the hosting consortium video channel. Virtual | COCO - 25 Jan 2023 |
25 Jan 12:30 pm 2:00 pmPython to C++ #2C++ is a high level programming language that is extremely useful for scientific applications. The language has historically had a bad reputation, but modern C++ is much improved so that your code can be relatively short and elegant. In this workshop we will teach the basics of C++ for people who are familiar with the basics of programming, and we will especially compare and contrast C++ with Python (only the material covered in SCMP142 "Intro to Programming with Python" is required). Knowing multiple programming languages may be a useful skill: while Python is a wonderful programming language, execution speed is often a practical issue for pure Python applications. For applications where this is an issue, coding in C++ can significantly improve performance. As C++ can relatively easily be integrated in a Python project, it is also possible (and common) to code just the bottleneck in that language.Format: In-person, but also will be broadcast and recorded. SciNet Teaching Room | SCMP241 - Jan 2023 |
26 Jan 11:00 am 12:00 pmScientific 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 |
26 Jan 11:00 am 12:30 pmEES1137 Lecture 6In 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 |
27 Jan 12:30 pm 2:00 pmPython to C++ #3C++ is a high level programming language that is extremely useful for scientific applications. The language has historically had a bad reputation, but modern C++ is much improved so that your code can be relatively short and elegant. In this workshop we will teach the basics of C++ for people who are familiar with the basics of programming, and we will especially compare and contrast C++ with Python (only the material covered in SCMP142 "Intro to Programming with Python" is required). Knowing multiple programming languages may be a useful skill: while Python is a wonderful programming language, execution speed is often a practical issue for pure Python applications. For applications where this is an issue, coding in C++ can significantly improve performance. As C++ can relatively easily be integrated in a Python project, it is also possible (and common) to code just the bottleneck in that language.Format: In-person, but also will be broadcast and recorded. SciNet Teaching Room | SCMP241 - Jan 2023 |
31 Jan 10:30 am 12:00 pmEES1137 Lecture 7In 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 |
31 Jan 11:00 am 12:00 pmScientific 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 |
| February,2023 | |
1 Feb 12:00 pm 1:00 pmCO Colloquium by Ching-Hsing Yu on "File Management - Packing Small Files"This week's colloquium: "File Management - Packing Small Files" by Ching-Hsing Yu from SciNet. 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 registration is required. Virtual | COCO - 1 Feb 2023 |
2 Feb 11:00 am 12:30 pmEES1137 Lecture 8In 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 |
2 Feb 11:00 am 12:00 pmScientific 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 |
7 Feb 10:30 am 12:00 pmEES1137 Lecture 9In 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 |
7 Feb 11:00 am 12:00 pmScientific 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 |
8 Feb 9:00 am 10:00 amBCH2202 - Lecture 1In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
8 Feb 10:00 am 11:30 amIntro to SciNet, Niagara and MistIn 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 - Feb 2023 |
9 Feb 11:00 am 12:30 pmEES1137 Lecture 10In 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 |
9 Feb 11:00 am 12:00 pmScientific 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 |
11 Feb 12:00 amIris data set problem is dueC++ is a high level programming language that is extremely useful for scientific applications. The language has historically had a bad reputation, but modern C++ is much improved so that your code can be relatively short and elegant. In this workshop we will teach the basics of C++ for people who are familiar with the basics of programming, and we will especially compare and contrast C++ with Python (only the material covered in SCMP142 "Intro to Programming with Python" is required). Knowing multiple programming languages may be a useful skill: while Python is a wonderful programming language, execution speed is often a practical issue for pure Python applications. For applications where this is an issue, coding in C++ can significantly improve performance. As C++ can relatively easily be integrated in a Python project, it is also possible (and common) to code just the bottleneck in that language.Format: In-person, but also will be broadcast and recorded. | SCMP241 - Jan 2023 |
13 Feb 1:00 pm 4:00 pmMS Windows Subsystem for LinuxWindows 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 SciNet Teaching Room | SCMP291 - Feb 2023 |
14 Feb 10:30 am 12:00 pmEES1137 Lecture 11In 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 |
14 Feb 11:00 am 12:00 pmScientific 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 |
15 Feb 9:00 am 10:00 amBCH2202 - Lecture 2In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
16 Feb 10:00 am 11:30 amEES1137 Lecture 12In 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 |
16 Feb 11:00 am 12:00 pmScientific 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 |
21 Feb 12:30 pm 2:00 pmIntro to GPU Programming #1An 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 the assignment.Format: In person, but also broadcast. SciNet Teaching Room | HPC133 - Feb 2023 |
22 Feb 9:00 am 10:00 amBCH2202 - Lecture 3In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
22 Feb 12:30 pm 2:00 pmIntro to GPU Programming #2An 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 the assignment.Format: In person, but also broadcast. SciNet Teaching Room | HPC133 - Feb 2023 |
24 Feb 1:30 pm 3:00 pmIntro to GPU Programming #3An 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 the assignment.Format: In person, but also broadcast. SciNet Teaching Room | HPC133 - Feb 2023 |
28 Feb 10:30 am 12:00 pmEES1137 Lecture 13In 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 |
28 Feb 11:00 am 12:00 pmScientific Computing Lecture (2023)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 |
| March,2023 | |
1 Mar 9:00 am 10:00 amBCH2202 - Lecture 4In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
2 Mar 10:00 am 11:30 amEES1137 Lecture 14In 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 |
2 Mar 11:00 am 12:00 pmScientific Computing (2023)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 |
7 Mar 10:30 am 12:00 pmEES1137 Lecture 15In 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 |
7 Mar 11:00 am 12:00 pmScientific Computing Lecture (2023)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 |
8 Mar 9:00 am 10:00 amBCH2202 - Lecture 5In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
9 Mar 10:00 am 11:30 amEES1137 Lecture 16In 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 |
9 Mar 11:00 am 12:00 pmScientific Computing (2023)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 |
13 Mar 1:00 pm 4:00 pmLinux Shell ScriptingLearn 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. SciNet Teaching Room | SCMP201 - Mar 2023 |
14 Mar 10:30 am 12:00 pmEES1137 Lecture 17In 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 |
14 Mar 11:00 am 12:00 pmScientific Computing Lecture (2023)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 |
15 Mar 9:00 am 10:00 amBCH2202 - Lecture 6In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
15 Mar 10:00 am 11:30 amIntro to SciNet, Niagara and MistIn 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: TBD (hopefully In-person), but also broadcast and recorded. SciNet Teaching Room | HPC105 - Mar 2023 |
16 Mar 11:00 am 12:00 pmScientific Computing (2023)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 Mar 11:00 am 12:30 pmEES1137 Lecture 18In 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 |
21 Mar 10:30 am 12:00 pmEES1137 Lecture 19In 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 |
21 Mar 11:00 am 12:00 pmScientific Computing Lecture (2023)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 |
22 Mar 9:00 am 10:00 amBCH2202 - Lecture 7In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
23 Mar 11:00 am 12:30 pmEES1137 Lecture 20In 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 |
23 Mar 11:00 am 12:00 pmScientific Computing (2023)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 |
27 Mar 1:00 pm 4:00 pmPython and High Performance ComputingParallel programming in Python. We will cover subprocess, numexpr, multiprocessing, MPI, and other parallel-enabling python packages.Format: In person, but also broadcast and recorded. SciNet Teaching Room | HPC111 - Mar 2023 |
28 Mar 10:30 am 12:00 pmEES1137 Lecture 21In 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 |
28 Mar 11:00 am 12:00 pmScientific Computing Lecture (2023)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 |
29 Mar 9:00 am 10:00 amBCH2202 - Lecture 8In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
30 Mar 11:00 am 12:30 pmEES1137 Lecture 22In 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 |
30 Mar 11:00 am 12:00 pmScientific Computing (2023)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 |
| April,2023 | |
4 Apr 10:30 am 12:00 pmEES1137 Lecture 23In 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 |
4 Apr 11:00 am 12:00 pmScientific Computing Lecture (2023)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 |
5 Apr 9:00 am 10:00 amBCH2202 - Lecture 9In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
6 Apr 11:00 am 12:30 pmEES1137 Lecture 24In 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 |
6 Apr 11:00 am 12:00 pmScientific Computing (2023)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 |
12 Apr 9:00 am 10:00 amBCH2202 - Lecture 10In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
12 Apr 10:00 am 11:30 amIntro to SciNet, Niagara and MistIn 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 - Apr 2023 |
17 Apr 1:00 pm 4:00 pmAdvanced GNU/Linux IIGNU tools provide powerful commands that facilitate the usage of HPC systems. This course explores some efficient ways of working with bash shell for routine tasks. It is complementary to the "Advanced Linux Command Line I". Attending this class requires basic knowledge of GNU/Linux shell. Format: TBD SciNet Teaching Room | SCMP281 - Apr 2023 |
19 Apr 9:00 am 10:00 amBCH2202 - Lecture 11In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
25 Apr 11:00 am 12:00 pmNeural Network Programming LectureThis six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Lectures will be 11:00am - 12:00pm, Tuesday and Thursdays.Format: In-person, but lectures will be recorded. SciNet Training Room | DAT112 - Apr 2023 |
26 Apr 9:00 am 10:00 amBCH2202 - Lecture 12In 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 students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |

