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March,2024
27 Mar 11:00 am 12:00 pm

Intro to Python for Biochemistry

In this course students will be instructed in how to program in Python. Ultimately students will learn how to use Python to analyze, process and visualize data. This course is designed for students with little to no experience in programming. This is a graduate course that can be taken for by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI.
BCH2203 - Winter 2024
28 Mar 11:00 am 12:00 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.
UTSC: IC120
EES1137 - Winter 2024Show in Google map
28 Mar 11:00 am 12:00 pm

PHY1610 Scientific Computing Lecture

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.This is an in-person course.
PHY1610 - Winter 2024
April,2024
2 Apr 10:00 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.
UTSC: AA207
EES1137 - Winter 2024Show in Google map
2 Apr 11:00 am 12:00 pm

PHY1610 Scientific Computing Lecture

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.This is an in-person course.
PHY1610 - Winter 2024
4 Apr 11:00 am 12:00 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.
UTSC: IC120
EES1137 - Winter 2024Show in Google map
4 Apr 11:00 am 12:00 pm

PHY1610 Scientific Computing Lecture

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.This is an in-person course.
PHY1610 - Winter 2024
10 Apr 11:00 am 12:00 pm

Intro to Python for Biochemistry

In this course students will be instructed in how to program in Python. Ultimately students will learn how to use Python to analyze, process and visualize data. This course is designed for students with little to no experience in programming. This is a graduate course that can be taken for by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI.
BCH2203 - Winter 2024
10 Apr 1:00 pm 2:30 pm

Intro to Niagara

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: Virtual Virtual
HPC105 - Apr 2024Show in Google map
15 Apr 1:00 pm 4:00 pm

Shell Scripting

Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.Note: this event has been moved from April 8th to April 15th.Format: Virtual Virtual
SCMP201 - Apr 2024Show in Google map
17 Apr 12:00 pm 1:00 pm

CO Colloquium "How to Buy a Supercomputer for Scientific Computing"

Buying a new supercomputer that both maximises total performance, given our budget, and whose architecture suits our users' workloads is a very difficult balancing act. There are a wide range of decisions to be made, such as: CPU architecture; node count; memory size/bandwidth; GPU count; interconnect type; storage size; filesystem type/bandwidth; cooling type and power budget to name but a few. In order to balance all of these constraints we need to come up with a scoring system to compare potential candidate supercomputers. In this talk we describe the Scalable System Improvement (SSI) metric and apply it to the system refresh of Niagara & Mist. Virtual
COCO - 17 Apr 2024Show in Google map
23 Apr 11:00 am 12:00 pm

DAT112: Lecture 1

Introduction to neural network programming, lecture 1
DAT112 - Apr 2024
25 Apr 11:00 am 12:00 pm

DAT112: Lecture 2

Introduction to neural network programming, lecture 2
DAT112 - Apr 2024
30 Apr 11:00 am 12:00 pm

DAT112: Lecture 3

Introduction to neural network programming, lecture 3
DAT112 - Apr 2024
May,2024
2 May 11:00 am 12:00 pm

DAT112: Lecture 4

Introduction to neural network programming, lecture 4
DAT112 - Apr 2024
7 May 11:00 am 12:00 pm

DAT112: Lecture 5

Introduction to neural network programming, lecture 5
DAT112 - Apr 2024
8 May 1:00 pm 2:30 pm

Intro to Niagara

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: Virtual Virtual
HPC105 - May 2024Show in Google map
9 May 11:00 am 12:00 pm

DAT112: Lecture 6

Introduction to neural network programming, lecture 6
DAT112 - Apr 2024
13 May 1:00 pm 4:00 pm

Relational Databases

Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.Prerequisites: Some Linux command line experience.  Python experience is strongly advised. Format: Virtual Virtual
SCMP231 - May 2024Show in Google map
14 May 11:00 am 12:00 pm

DAT112: Lecture 7

Introduction to neural network programming, lecture 7
DAT112 - Apr 2024
16 May 11:00 am 12:00 pm

DAT112: Lecture 8

Introduction to neural network programming, lecture 8
DAT112 - Apr 2024
21 May 11:00 am 12:00 pm

DAT112: Lecture 9

Introduction to neural network programming, lecture 9
DAT112 - Apr 2024
23 May 11:00 am 12:00 pm

DAT112: Lecture 10

Introduction to neural network programming, lecture 10
DAT112 - Apr 2024
27 May 1:00 pm 4:00 pm

Bash idioms, awk, etc.

This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.Format: Virtual
SCMP281 - May 2024
28 May 11:00 am 12:00 pm

DAT112: Lecture 11

Introduction to neural network programming, lecture 11
DAT112 - Apr 2024
30 May 11:00 am 12:00 pm

DAT112: Lecture 12

Introduction to neural network programming, lecture 12
DAT112 - Apr 2024
June,2024
3 Jun 9:00 am 12:00 pm

CO Summer School S2: Data Preparation

This course provides you with essential knowledge and skills to effectively prepare data for analysis. Starting with an overview of the Data Analytics pipeline and processes, the course explores various statistical and visualization techniques used in Exploratory and Descriptive Analytics to understand historical data. You will then delve into the art of Data Preparation, gaining expertise in data cleaning, handling missing values, detecting, and handling outliers, as well as transforming and engineering features. By the end of the course, you will be equipped with the necessary tools to ensure data quality and integrity, enabling you to make informed decisions and derive valuable insights from their data. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic Python (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
3 Jun 9:00 am 12:00 pm

CO Summer School S1: Introduction to Linux shell (morning session)

Running programs on the supercomputers is done via the BASH shell. This course is two three hour live demos on using bash. No prior familiarity with bash is assumed. In addition to the basics of getting around, globbing, regular expressions, redirection, pipes, and scripting will be covered. A series of exercises are required to be done in order to complete the course. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
3 Jun 1:30 pm 4:30 pm

CO Summer School S2: Data Security

Be aware. Stay secure. Join us to learn more about the tools you can use to prevent the theft of your data and possibly of your identity. Other topics of discussion will include common hacking attempts, how to recognize them, and how to avoid having your data compromised, stolen, or destroyed. We will also talk about data encryption and provide tips for when travelling with electronic devices. Level: Introductory Length: 3 hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
3 Jun 1:30 pm 4:30 pm

CO Summer School S1: Introduction to Linux shell (afternoon session)

Running programs on the supercomputers is done via the BASH shell. This course is two three hour live demos on using bash. No prior familiarity with bash is assumed. In addition to the basics of getting around, globbing, regular expressions, redirection, pipes, and scripting will be covered. A series of exercises are required to be done in order to complete the course. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map