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March,2023
30 Mar 11:00 am 12:30 pm

EES1137 Lecture 22

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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 must enrol through Acorn/ROSI.
EES1137 - Winter 2023
30 Mar 11:00 am 12:00 pm

Scientific Computing (2023)

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, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
April,2023
4 Apr 10:30 am 12:00 pm

EES1137 Lecture 23

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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 must enrol through Acorn/ROSI.
EES1137 - Winter 2023
4 Apr 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

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, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
6 Apr 11:00 am 12:00 pm

Scientific Computing (2023)

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, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
6 Apr 11:00 am 12:30 pm

EES1137 Lecture 24

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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 must enrol through Acorn/ROSI.
EES1137 - Winter 2023
12 Apr 10:00 am 11:30 am

Intro to SciNet, Niagara and Mist

In about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.Format: In-person, as well as broadcast and recorded. SciNet Teaching Room
HPC105 - Apr 2023Show in Google map
17 Apr 1:00 pm 4:00 pm

Advanced GNU/Linux II

GNU tools provide powerful commands that facilitate the usage of HPC systems. This course explores some efficient ways of working with bash shell for routine tasks. It is complementary to the "Advanced Linux Command Line I". Attending this class requires basic knowledge of GNU/Linux shell. Format: TBD SciNet Teaching Room
SCMP281 - Apr 2023Show in Google map
25 Apr 11:00 am 12:00 pm

Neural Network Programming Lecture

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.  Lectures will be 11:00am - 12:00pm, Tuesday and Thursdays.Format: In-person, but lectures will be recorded. SciNet Training Room
DAT112 - Apr 2023Show in Google map
27 Apr 10:04 am 11:04 am

Neural Network Programming Lecture

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.  Lectures will be 11:00am - 12:00pm, Tuesday and Thursdays.Format: In-person, but lectures will be recorded. SciNet Teaching Room
DAT112 - Apr 2023Show in Google map