SciNet Events |
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| March,2020 | |
|---|---|
Tue 3rd Mar 11:00 am 12:00 pm | 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, ...). Part of Scientific Computing for Physicists, Location: SciNet Teaching Room MaRS 1140  661 University Ave., Toronto, M5G 1M1, Canada |
Wed 4th Mar 11:00 am 12:00 pm | In this course data analysis techniques utilizing Python and R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing.The goal of this course is to prepare graduate students to perform 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 have to enroll through Acorn/ROSI.This course is part of the EES graduate program and to be taught at the UTSc campus. Location: MW 140 (UTSC) Social Sciences Building @ UTSC, Scarborough, M1C 1A4, Canada |
Thu 5th Mar 11:00 am 12:00 pm | 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, ...). Part of Scientific Computing for Physicists, Location: SciNet Teaching Room MaRS 1140 661 University Ave., Toronto, M5G 1M1, Canada |
Fri 6th Mar 11:00 am 12:00 pm | In this course data analysis techniques utilizing Python and R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing.The goal of this course is to prepare graduate students to perform 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 have to enroll through Acorn/ROSI.This course is part of the EES graduate program and to be taught at the UTSc campus. Location: MW 160 (UTSC) Social Sciences Building @ UTSC, Scarborough, M1C 1A4, Canada |
Tue 10th Mar 11:00 am 12:00 pm | 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, ...). Part of Scientific Computing for Physicists, Location: SciNet Teaching Room MaRS 1140 661 University Ave., Toronto, M5G 1M1, Canada |
Wed 11th Mar 10:00 am 11:30 am | A quick introduction how to use SciNet and the Niagara supercomputer. Location: SciNet Boardroom MaRS 1140 661 University Ave., Toronto, M5G 1M1, Canada |
Wed 11th Mar 11:00 am 12:00 pm | In this course data analysis techniques utilizing Python and R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing.The goal of this course is to prepare graduate students to perform 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 have to enroll through Acorn/ROSI.This course is part of the EES graduate program and to be taught at the UTSc campus. Location: MW 140 (UTSC) Social Sciences Building @ UTSC, Scarborough, M1C 1A4, Canada |
Wed 11th Mar 12:00 pm 1:00 pm | Monthly user meeting at SciNet with pizza, a techtalk (TBA) and user discussion. Location: SciNet Teaching Room MaRS 1140 661 University Ave., Toronto, M5G 1M1, Canada |
Thu 12th Mar 11:00 am 12:00 pm | 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, ...). Part of Scientific Computing for Physicists, Location: SciNet Teaching Room MaRS 1140 661 University Ave., Toronto, M5G 1M1, Canada |
Fri 13th Mar 11:00 am 12:00 pm | In this course data analysis techniques utilizing Python and R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing.The goal of this course is to prepare graduate students to perform 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 have to enroll through Acorn/ROSI.This course is part of the EES graduate program and to be taught at the UTSc campus. Location: MW 160 (UTSC) Social Sciences Building @ UTSC, Scarborough, M1C 1A4, Canada |
