Research data management

Practical data management courses
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Courses tagged with "Research data management"

Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration.  In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.

Format: Virtual

Teacher: James Willis
Category: Data Science
Date: Wed, 6 Nov 2024 - 1:00 pm
Data Science Credits: 3

Managing large amounts of data can be a challenging task. Processing large numbers of files incur heavy overhead of IO communications. This course explores several options such as using Apptainer Overlay and SQLite to pack and reduce a large number of files to few files, and hence, improving IO performance. Python scripts are used throughout the course.

Format: Virtual

Category: Data Science
Date: Mon, 15 Jan 2024 - 1:00 pm
Data Science Credits: 3

Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration.  In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.

Format: Virtual

Teacher: James Willis
Category: Data Science
Date: Mon, 20 Nov 2023 - 1:00 pm
Data Science Credits: 3

Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration.  In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.
Format: In-person, but also will be broadcast and recorded.

Teacher: James Willis
Category: Data Science
Date: Mon, 21 Nov 2022 - 1:00 pm
Data Science Credits: 3

Managing large amounts of data can be a challenging task. Processing large numbers of files incur heavy overhead of IO communications. This course explores several options such as using Apptainer Overlay and SQLite to pack and reduce a large number of files to few files, and hence, improving IO performance. Python scripts are used throughout the course.

Format: On-line (Zoom).

Category: Data Science
Date: Mon, 28 Nov 2022 - 1:00 pm
Data Science Credits: 3

Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration.  In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.

Teacher: James Willis
Category: Data Science
Date: Tue, 15 Mar 2022 - 1:00 pm
Data Science Credits: 3
Introductory workshop to get started in the usage of version control GIT. This workshop is held in collaboration with UofT-Libraries.
Category: Data Science
Date: Fri, 4 Oct 2019 - 1:00 pm
Learn how to pinpoint and alleviate bottlenecks in large data-driven research projects. Techniques such as tar, compression, ramdisk, and file format options will be covered.
Category: Data Science
Date: Wed, 17 May 2017 - 10:00 am
Scientific Computing Credits: 2
Data Science Credits: 6
Learn how to pinpoint and alleviate bottlenecks in large data-driven research projects. Techniques such as tar, compression, ramdisk, file format options, and job scheduling techniques will be covered.
Teacher: SciNet Team
Category: Data Science
Date: Wed, 21 Sep 2016 - 9:30 am
Trends and tools in research data management.
Category: Data Science
Date: Wed, 25 May 2016 - 1:30 pm
Scientific Computing Credits: 1
Data Science Credits: 3
Learn how to pinpoint and alleviate bottlenecks in large data-driven research projects. Techniques such as tar, compression, ramdisk, file format options, and job scheduling techniques will be covered.
Category: Data Science
Date: Wed, 20 Apr 2016 - 9:30 am