 |
  |
| October,2023 | |
|---|---|
10 Oct 9:00 am 10:30 amMSC1090 lecture 9The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in SS1085. Students willing to take the course as part of their graduate program must enrol through Acorn. This course is part of the IMS graduate program. SS1085 | MSC1090 - Fall 2023 |
10 Oct 1:00 pm 2:00 pmIntro to Programming SessionNew 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.Format: In-person. Sessions will be recorded. SciNet Teaching Room | SCMP142 - Oct 2023 |
11 Oct 12:00 pm 1:00 pmCO Colloquium: High-Performance Computing in RIn the world where data has become extremely important, scientists require tools to process large volumes of data efficiently. R became increasingly popular in recent years for data processing, statistical analysis, and data science. In this session we will discuss tools that measure the performance of an R code, so that we can understand the nature of performance issues. We will also describe techniques that will improve the computational speed of R code. Basic knowledge of programming in R will be assumed. On-line | COCO - 11 Oct 2023 |
11 Oct 12:00 pm 1:00 pmCO Colloquium: High-Performance Computing in RIn the world where data has become extremely important, scientists require tools to process large volumes of data efficiently. R became increasingly popular in recent years for data processing, statistical analysis, and data science. In this session we will discuss tools that measure the performance of an R code, so that we can understand the nature of performance issues. We will also describe techniques that will improve the computational speed of R code. Basic knowledge of programming in R will be assumed. On-line | COCO - 25 Oct 2023 |
11 Oct 12:00 pm 1:00 pmCO Colloquium: High-Performance Computing in RIn the world where data has become extremely important, scientists require tools to process large volumes of data efficiently. R became increasingly popular in recent years for data processing, statistical analysis, and data science. In this session we will discuss tools that measure the performance of an R code, so that we can understand the nature of performance issues. We will also describe techniques that will improve the computational speed of R code. Basic knowledge of programming in R will be assumed. On-line | COCO - 22 Nov 2023 |
11 Oct 12:00 pm 1:00 pmCO Colloquium: High-Performance Computing in RIn the world where data has become extremely important, scientists require tools to process large volumes of data efficiently. R became increasingly popular in recent years for data processing, statistical analysis, and data science. In this session we will discuss tools that measure the performance of an R code, so that we can understand the nature of performance issues. We will also describe techniques that will improve the computational speed of R code. Basic knowledge of programming in R will be assumed. On-line | COCO - 8 Nov 2023 |
11 Oct 12:00 pm 1:00 pmCO Colloquium: High-Performance Computing in RIn the world where data has become extremely important, scientists require tools to process large volumes of data efficiently. R became increasingly popular in recent years for data processing, statistical analysis, and data science. In this session we will discuss tools that measure the performance of an R code, so that we can understand the nature of performance issues. We will also describe techniques that will improve the computational speed of R code. Basic knowledge of programming in R will be assumed. On-line | COCO - 6 Dec 2023 |
11 Oct 1:00 pm 2:30 pmIntro to NiagaraIn 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 - Oct 2023 |
12 Oct 9:00 am 10:30 amMSC1090 lecture 10The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in SS1085. Students willing to take the course as part of their graduate program must enrol through Acorn. This course is part of the IMS graduate program. SS1085 | MSC1090 - Fall 2023 |
12 Oct 1:00 pm 2:00 pmIntro to Programming SessionNew 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.Format: In-person. Sessions will be recorded. SciNet Teaching Room | SCMP142 - Oct 2023 |

