Upcoming SciNet Events

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September,2018
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
Tue 2nd Oct
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 4th Oct
12:00 pm
1:30 pm
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This is the English language Q&A session for Compute Canada's competition for the compute and storage resource allocations for 2019 (RAC). Part of Compute Canada Resource Allocation Competition for 2019 Info Session, Location: SciNet Boardroom MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 4th Oct
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 4th 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
Tue 9th 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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 9th Oct
1:00 pm
2:00 pm
Add event to google
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 10th Oct
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 10th Oct
12:00 pm
1:00 pm
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Pizza and discussion about the Resource Allocation Competition Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 11th 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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Thu 11th Oct
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 16th Oct
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 16th Oct
1:00 pm
2:00 pm
Add event to google
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
Wed 17th Oct
1:00 pm
4:00 pm
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Learn how to write bash script, use environment variables, how to control process, and much more. Requires some linux basic command line experience. Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 18th Oct
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 18th Oct
1:00 pm
2:00 pm
Add event to google
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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 23rd 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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 23rd Oct
1:00 pm
2:00 pm
Add event to google
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 25th Oct
1:00 pm
2:00 pm
Add event to google
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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Thu 25th Oct
1:00 pm
2:00 pm
Add event to google
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 30th Oct
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
November,2018
Thu 1st Nov
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 6th Nov
1:00 pm
2:00 pm
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Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Tue 6th Nov
1:00 pm
2:00 pm
Add event to google
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 8th Nov
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 8th Nov
1:00 pm
2:00 pm
Add event to google
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 13th Nov
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 14th Nov
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
Thu 15th Nov
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 20th Nov
1:00 pm
2:00 pm
Add event to google
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 20th Nov
1:00 pm
2:00 pm
Add event to google
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 21st Nov
12:00 pm
1:00 pm
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Pizza and presentation by PhD student Stephanie Penk: "Making a modeler; on the use  of supercomputers in ecological systems." Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 21st Nov
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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Thu 22nd Nov
1:00 pm
2:00 pm
Add event to google
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 22nd Nov
1:00 pm
2:00 pm
Add event to google
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 27th Nov
1:00 pm
2:00 pm
Add event to google
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 27th Nov
1:00 pm
2:00 pm
Add event to google
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 29th Nov
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
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Thu 29th Nov
1:00 pm
2:00 pm
Add event to google
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
December,2018
Tue 4th Dec
1:00 pm
2:00 pm
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Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Thu 6th Dec
1:00 pm
2:00 pm
Add event to google
Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
January,2019
Tue 8th Jan
11:00 am
12:00 pm
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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, ...). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 9th Jan
11:00 am
12:00 pm
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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: HL 006 (UTSC)
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Highland Hall @ UTSC, Scarborough, Canada
Thu 10th Jan
11:00 am
12:00 pm
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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, ...). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Fri 11th Jan
11:00 am
12:00 pm
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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: HL 008 (UTSC)
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Highland Hall @ UTSC, Scarborough, Canada
Tue 15th Jan
11:00 am
12:00 pm
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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, ...). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 16th Jan
10:00 am
11:30 am
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A quick introduction how to use SciNet and the Niagara supercomputer. Location: SciNet Boardroom MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 16th Jan
11:00 am
12:00 pm
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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: HL 006 (UTSC)
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Highland Hall @ UTSC, Scarborough, Canada
Wed 16th Jan
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 pr Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 17th Jan
11:00 am
12:00 pm
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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, ...). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Fri 18th Jan
11:00 am
12:00 pm
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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: HL 008 (UTSC)
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Highland Hall @ UTSC, Scarborough, Canada
Tue 22nd Jan
11:00 am
12:00 pm
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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, ...). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 23rd Jan
11:00 am
12:00 pm
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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: HL 006 (UTSC)
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Highland Hall @ UTSC, Scarborough, Canada
Thu 24th Jan
11:00 am
12:00 pm
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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, ...). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Fri 25th Jan
9:00 am
5:00 pm
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The Institute for Data Intensive Engineering and Sciences will jointly host a Visualization Hackathon with the University of Toronto. The Hackathon will be on Friday & Saturday, January 25 & 26, 2019 from 9 AM – 5 PM (approx), with sessions and presentations at both Homewood Campus at JHU, and SciNet headquarters at the University of Toronto. We will focus on topics and techniques relevant to data-intensive and computationally-intensive research. This event will feature some presentations on techniques and tools, but will be primarily hands on and participant driven.idies.jhu.edu/idies-to-.....-form Part of IDIES Visualization Hackathon, Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada