Upcoming SciNet Events

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September,2017
Mon 18th Sep
1:00 pm
2:00 pm
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Explore and use advanced examples of parallel computing in scientific research (mini/modular graduate course). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Tue 19th Sep
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
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1 King's College Circle, Toronto, M5S 1A8, Canada
Wed 20th Sep
1:00 pm
2:00 pm
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Explore and use advanced examples of parallel computing in scientific research (mini/modular graduate course). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 21st Sep
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
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164 College Street, Toronto
Mon 25th Sep
10:00 am
3:00 pm
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This workshop will introduce neural network programming concepts, theory and techniques. The level of the material will be introductory, intended for those with no experience with neural networks. The programming language will be Python 2.7; experience with Python programming will be assumed. The Keras neural network framework, with a Theano back end, will be used for more-advanced programming; no experience with Keras or Theano will be expected. Students should come with the following Python packages installed on their laptops: numpy, matplotlib, scikit-learn, theano (version 0.9.0 or greater), keras. Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Mon 25th Sep
1:00 pm
2:00 pm
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Explore and use advanced examples of parallel computing in scientific research (mini/modular graduate course). Location: SciNet Boardroom MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Tue 26th Sep
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
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1 King's College Circle, Toronto, M5S 1A8, Canada
Wed 27th Sep
10:00 am
12:00 pm
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Learn the basics of how to use the unix shell in two hours. Very useful for new users of SciNet that have little or no experience with unix or linux. Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Wed 27th Sep
1:00 pm
2:00 pm
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Explore and use advanced examples of parallel computing in scientific research (mini/modular graduate course). Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 28th Sep
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
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164 College Street, Toronto
October,2017
Mon 2nd Oct
11:00 am
12:00 pm
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This class will review advanced neural network programming theory and architectures. The level of the material will not be introductory, experience with neural networks will be assumed. This class is intended to continue the material covered in DAT111 (Introduction to Neural Network Programming). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Mon 2nd Oct
1:00 pm
2:00 pm
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Explore and use advanced examples of parallel computing in scientific research (mini/modular graduate course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 3rd Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Wed 4th Oct
1:00 pm
2:00 pm
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Explore and use advanced examples of parallel computing in scientific research (mini/modular graduate course). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Thu 5th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
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164 College Street, Toronto
Tue 10th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
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1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 10th 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
Wed 11th Oct
12:00 pm
1:30 pm
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Compute Canada has announced its competition for the 2018 compute and storage resource allocation (RAC).PIs of groups that require more than a default account, should consider submitting a proposal. The deadline is November 16th, 2017.If you're new to the RAC application process, or want to know what is different this year, SciNet will be broadcasting the online information session regarding the application process.Users can participate also online visiting the previous website and registering online.SciNet analyst will be available on site during the online information session, and will answer any questions you might have. Part of 2018 RAC Information Session, Location: SciNet Boardroom MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 12th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 12th 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
Thu 12th Oct
4:00 pm
6:00 pm
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Information sessions for the 2018 Big Data Challenge for High Schools Students. Part of 2017-18 Big Data Orientation Session, Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Fri 13th Oct
2:00 pm
3:00 pm
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Introductory seminar series on Scientific Computing, High-Performance Computing, Data Science and Visualization; this lecture series is part of the "Research Project Course" (PHY479Y1) for 4th year undergraduate physics students. Part of Undergrad Seminars on Advanced Research Computing, Data Science and Visualization, Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Mon 16th Oct
11:00 am
12:00 pm
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This class will review advanced neural network programming theory and architectures. The level of the material will not be introductory, experience with neural networks will be assumed. This class is intended to continue the material covered in DAT111 (Introduction to Neural Network Programming). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 17th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 17th 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 19th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 19th 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
Fri 20th Oct
2:00 pm
3:00 pm
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Introductory seminar series on Scientific Computing, High-Performance Computing, Data Science and Visualization; this lecture series is part of the "Research Project Course" (PHY479Y1) for 4th year undergraduate physics students. Part of Undergrad Seminars on Advanced Research Computing, Data Science and Visualization, Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 24th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 24th 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
Wed 25th 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 26th Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 26th 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
Fri 27th Oct
2:00 pm
3:00 pm
Add event to google
Introductory seminar series on Scientific Computing, High-Performance Computing, Data Science and Visualization; this lecture series is part of the "Research Project Course" (PHY479Y1) for 4th year undergraduate physics students. Part of Undergrad Seminars on Advanced Research Computing, Data Science and Visualization, Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Mon 30th Oct
11:00 am
12:00 pm
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This class will review advanced neural network programming theory and architectures. The level of the material will not be introductory, experience with neural networks will be assumed. This class is intended to continue the material covered in DAT111 (Introduction to Neural Network Programming). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 31st Oct
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 31st 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
November,2017
Thu 2nd Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 2nd Nov
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
Fri 3rd Nov
2:00 pm
3:00 pm
Add event to google
Introductory seminar series on Scientific Computing, High-Performance Computing, Data Science and Visualization; this lecture series is part of the "Research Project Course" (PHY479Y1) for 4th year undergraduate physics students. Part of Undergrad Seminars on Advanced Research Computing, Data Science and Visualization, Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 7th Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
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1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 7th 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
Wed 8th Nov
12:00 pm
1:00 pm
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Pizza, user discussion and a talk about the details of the new Niagara supercomputer and its deployment at SciNet this fall.- 60 minutes Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Thu 9th Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 9th 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
Mon 13th Nov
11:00 am
12:00 pm
Add event to google
This class will review advanced neural network programming theory and architectures. The level of the material will not be introductory, experience with neural networks will be assumed. This class is intended to continue the material covered in DAT111 (Introduction to Neural Network Programming). Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 14th Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 14th 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
Thu 16th Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 16th 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
Fri 17th Nov
2:00 pm
3:00 pm
Add event to google
Introductory seminar series on Scientific Computing, High-Performance Computing, Data Science and Visualization; this lecture series is part of the "Research Project Course" (PHY479Y1) for 4th year undergraduate physics students. Part of Undergrad Seminars on Advanced Research Computing, Data Science and Visualization, Location: SciNet Teaching Room MaRS 1140
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Tue 21st Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
Show in Google map
1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 21st 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
Thu 23rd Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
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164 College Street, Toronto
Thu 23rd 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
Fri 24th Nov
2:00 pm
3:00 pm
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Introductory seminar series on Scientific Computing, High-Performance Computing, Data Science and Visualization; this lecture series is part of the "Research Project Course" (PHY479Y1) for 4th year undergraduate physics students. Part of Undergrad Seminars on Advanced Research Computing, Data Science and Visualization, Location: SciNet Teaching Room MaRS 1140
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661 University Ave., Toronto, M5G 1M1, Canada
Tue 28th Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Medical Sciences Building, MS2173
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1 King's College Circle, Toronto, M5S 1A8, Canada
Tue 28th 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
Show in Google map
661 University Ave., Toronto, M5G 1M1, Canada
Thu 30th Nov
11:00 am
12:00 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 Clinical BioStatistics, Location: Rosebrugh Building, RS211
Show in Google map
164 College Street, Toronto
Thu 30th 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