Upcoming SciNet Events

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March,2021
Mon 15th Mar
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 16th Mar
10:30 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. Part of Quantitative Applications for Data Analysis, Location: SciNet Online
Tue 16th Mar
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Thu 18th Mar
11:00 am
12:30 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. Part of Quantitative Applications for Data Analysis, Location: SciNet Online
Thu 18th Mar
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Mon 22nd Mar
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 23rd Mar
10:30 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. Part of Quantitative Applications for Data Analysis, Location: SciNet Online
Tue 23rd Mar
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Thu 25th Mar
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Thu 25th Mar
11:00 am
12:30 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. Part of Quantitative Applications for Data Analysis, Location: SciNet Online
Mon 29th Mar
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 30th Mar
10:30 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. Part of Quantitative Applications for Data Analysis, Location: SciNet Online
Tue 30th Mar
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
April,2021
Thu 1st Apr
11:00 am
12:30 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. Part of Quantitative Applications for Data Analysis, Location: SciNet Online
Thu 1st Apr
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Mon 5th Apr
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 6th Apr
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Thu 8th Apr
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, ...). Part of Scientific Computing for Physicists, Location: SciNet Online
Mon 12th Apr
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Wed 14th Apr
10:00 am
11:30 am
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A quick introduction how to use SciNet and the Niagara and Mist supercomputers. Location: SciNet Online
Wed 14th Apr
12:00 pm
1:00 pm
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Monthly (virtual) user meeting at SciNet with user discussion and a TechTalk. The topic on 14 April 2021 will be the new "Rouge" cluster at SciNet, donated as part of the AMD COVID-19 HPC Fund. Location: SciNet Online
Mon 19th Apr
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Mon 26th Apr
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 27th Apr
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Thu 29th Apr
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
May,2021
Mon 3rd May
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 4th May
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Thu 6th May
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Mon 10th May
1:00 pm
2:00 pm
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This course is an introductory course in programming utilizing the R Statistical Language.The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator. Part of Introduction to Programming with R, Location: SciNet Online
Tue 11th May
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Wed 12th May
10:00 am
11:30 am
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A quick introduction how to use SciNet and the Niagara and Mist supercomputers. Location: SciNet Online
Thu 13th May
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Tue 18th May
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Thu 20th May
11:00 am
12:00 pm
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This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online
Tue 25th May
11:00 am
12:00 pm
Add event to google
This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Part of Neural Network Programming, Location: SciNet Online