April,2024 | |
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2 Apr 10:00 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. UTSC: AA207 | EES1137 - Winter 2024 |
2 Apr 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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.This is an in-person course. | PHY1610 - Winter 2024 |
4 Apr 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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.This is an in-person course. | PHY1610 - Winter 2024 |
4 Apr 11:00 am 12:00 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. UTSC: IC120 | EES1137 - Winter 2024 |
8 Apr 1:16 pm 2:46 pmShell ScriptingLearn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.Format: Virtual Virtual | SCMP201 - Apr 2024 |
10 Apr 1:00 pm 2:30 pmIntro to NiagaraIn 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: Virtual Virtual | HPC105 - Apr 2024 |
23 Apr 11:00 am 12:00 pmDAT112: Lecture 1Introduction to neural network programming, lecture 1 | DAT112 - Apr 2024 |
25 Apr 11:00 am 12:00 pmDAT112: Lecture 2Introduction to neural network programming, lecture 2 | DAT112 - Apr 2024 |
30 Apr 11:00 am 12:00 pmDAT112: Lecture 3Introduction to neural network programming, lecture 3 | DAT112 - Apr 2024 |
May,2024 | |
2 May 11:00 am 12:00 pmDAT112: Lecture 4Introduction to neural network programming, lecture 4 | DAT112 - Apr 2024 |
7 May 11:00 am 12:00 pmDAT112: Lecture 5Introduction to neural network programming, lecture 5 | DAT112 - Apr 2024 |
8 May 1:00 pm 2:30 pmIntro to NiagaraIn 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: Virtual Virtual | HPC105 - May 2024 |
9 May 11:00 am 12:00 pmDAT112: Lecture 6Introduction to neural network programming, lecture 6 | DAT112 - Apr 2024 |
13 May 1:00 pm 4:00 pmRelational DatabasesPrinciples and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.Format: Virtual Virtual | SCMP231 - May 2024 |
14 May 11:00 am 12:00 pmDAT112: Lecture 7Introduction to neural network programming, lecture 7 | DAT112 - Apr 2024 |
16 May 11:00 am 12:00 pmDAT112: Lecture 8Introduction to neural network programming, lecture 8 | DAT112 - Apr 2024 |
21 May 11:00 am 12:00 pmDAT112: Lecture 9Introduction to neural network programming, lecture 9 | DAT112 - Apr 2024 |
23 May 11:00 am 12:00 pmDAT112: Lecture 10Introduction to neural network programming, lecture 10 | DAT112 - Apr 2024 |
27 May 1:00 pm 2:30 pmBash idioms, awk, etc.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 | SCMP281 - May 2024 |
28 May 11:00 am 12:00 pmDAT112: Lecture 11Introduction to neural network programming, lecture 11 | DAT112 - Apr 2024 |
30 May 11:00 am 12:00 pmDAT112: Lecture 12Introduction to neural network programming, lecture 12 | DAT112 - Apr 2024 |
June,2024 | |
12 Jun 1:00 pm 2:30 pmIntro to NiagaraIn 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: Virtual Virtual | HPC105 - Jun 2024 |