Upcoming SciNet Events

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September,2018
Tue 11th Sep
1:00 pm
2:00 pm
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In this course data analysis techniques utilizing the 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: 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 IMS graduate program and to be taught at the UofT St. George campus. Part of Introduction to Computational BioStatistics with R, Location: Medical Science Building, MSB4279
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1 King's College Circle, Toronto, M5S 1A8, Canada
Wed 12th Sep
10:00 am
12:00 pm
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A quick introduction how to use the new supercomputer Niagara. Part of Intro to SciNet/Niagara, Location: SciNet Boardroom MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 12th Sep
12:00 pm
1:30 pm
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George Stein (Dept. of Astronomy-UofT, CITA) "Machine learning cosmic structure formation" + pizzaAbstract:In modern astrophysics and cosmology, accurate simulations of the large scale structure of the universe are necessary. Usually, this is accomplished by so called N-body simulations, which calculate the full gravitational collapse of a region of the universe over its 14 billion year history. Instead of calculating this costly gravitational evolution, we trained a three-dimensional deep Convolutional Neural Network (CNN) to identify dark matter proto-haloes directly from the cosmological initial conditions, and showed that a CNN of this type can be a viable alternative in some cases. In this talk I will discuss current cosmological simulations and the invasion of machine learning techniques, with a focus on our work.For more information see https://arxiv.org/abs/1805.04537Please register for pizza purposes! Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 13th Sep
1:00 pm
2:00 pm
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In this course data analysis techniques utilizing the 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: 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 IMS graduate program and to be taught at the UofT St. George campus. Part of Introduction to Computational BioStatistics with R, Location: Medical Science Building, MSB4279
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1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 18th Sep
1:00 pm
2:00 pm
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In this course data analysis techniques utilizing the 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: 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 IMS graduate program and to be taught at the UofT St. George campus. Part of Introduction to Computational BioStatistics with R, Location: Medical Science Building, MSB4279
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1 King's College Circle, Toronto, M5S 1A8, Canada
Wed 19th Sep
1:00 pm
4:00 pm
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Working with many of the HPC systems in Ontario 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 course. This hands on session will cover basic commands and scripting. It could be a great boon for your productivity! Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 20th Sep
1:00 pm
2:00 pm
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In this course data analysis techniques utilizing the 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: 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 IMS graduate program and to be taught at the UofT St. George campus. Part of Introduction to Computational BioStatistics with R, Location: Medical Science Building, MSB4279
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1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 25th Sep
1:00 pm
2:00 pm
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In this course data analysis techniques utilizing the 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: 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 IMS graduate program and to be taught at the UofT St. George campus. Part of Introduction to Computational BioStatistics with R, Location: Medical Science Building, MSB4279
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1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 27th Sep
1:00 pm
2:00 pm
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In this course data analysis techniques utilizing the 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: 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 IMS graduate program and to be taught at the UofT St. George campus. Part of Introduction to Computational BioStatistics with R, Location: Medical Science Building, MSB4279
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1 King's College Circle, Toronto, M5S 1A8, Canada
October,2018
Tue 2nd Oct
1:00 pm
2:00 pm
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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. Part of Introduction to Programming with Python, Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada