Difference between revisions of "TrainingBlocks"
From Bioinformatics Core Wiki
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+ | {{TrainingBlock | ||
+ | |Title=Advanced linux course for biologists and genomics data formats | ||
+ | |Description=Two three-hour sessions to understand some of the main genomics data formats (fasta, fastq, gtf, bed...) and to learn how to parse them. Course material available [https://biocorecrg.github.io/advanced_linux_2019/ here]. | ||
+ | |Color=#ffcce6 | ||
+ | |TitleColor=#2E2E2E | ||
+ | |FontColor=#2E2E2E | ||
+ | |Image=Linux image.jpg | ||
+ | }} | ||
+ | {{TrainingBlock | ||
+ | |Title=CRG course: Introduction to R and exploratory data analysis - February/March 2019 | ||
+ | |Description=The eight three and a half-hour hands-on sessions of how to use R-Studio, learn and practice the basics in R, perform plotting and exploratory data analysis. Course material: | ||
+ | [https://biocorecrg.github.io/CRG_RIntroduction/ here] | ||
+ | |Color=#ccf5ff | ||
+ | |TitleColor=#2E2E2E | ||
+ | |FontColor=#2E2E2E | ||
+ | |Image=R Logo.png | ||
+ | }} | ||
+ | {{TrainingBlock | ||
+ | |Title=Introduction to containers - December 2018 and January 2019 | ||
+ | |Description=The two four-hour hands-on sessions of how to create and use containers (Docker and Singularity). | ||
+ | Course material: | ||
+ | [https://github.com/biocorecrg/containers-course here] | ||
+ | |Color=#ffd480 | ||
+ | |TitleColor=#2E2E2E | ||
+ | |FontColor=#2E2E2E | ||
+ | |Image= | ||
+ | }} | ||
{{TrainingBlock | {{TrainingBlock | ||
|Title=CRG course: Introduction to R - March/April 2018 | |Title=CRG course: Introduction to R - March/April 2018 | ||
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{{TrainingBlock | {{TrainingBlock | ||
|Title=CRG course "Introduction to R" | |Title=CRG course "Introduction to R" | ||
− | |Description=12h | + | |Description=12h very slow paced hands-on to learn how to use R. For more information, course materials, and links to external teaching resources, |
'''[[CRG_Introduction_to_R_July2017|visit the course website]]'''. | '''[[CRG_Introduction_to_R_July2017|visit the course website]]'''. | ||
|Color=#ecd8f9 | |Color=#ecd8f9 | ||
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|FontColor=#2E2E2E | |FontColor=#2E2E2E | ||
|Image=Linux image.jpg | |Image=Linux image.jpg | ||
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[[Category:TrainingBlocks| ]] | [[Category:TrainingBlocks| ]] |
Revision as of 16:06, 29 March 2019
Contents
- 1 Advanced linux course for biologists and genomics data formats
- 2 CRG course: Introduction to R and exploratory data analysis - February/March 2019
- 3 Introduction to containers - December 2018 and January 2019
- 4 CRG course: Introduction to R - March/April 2018
- 5 CRG PhD Course 2017-2018 "Introduction to Statistics in R"
- 6 CRG course "Introduction to R"
- 7 CRG course "Introduction to Statistics and R programming", May - June, 2017
- 8 CRG PhD/Master course 2016-2017 "Introduction to Statistics in R"
- 9 BIST Course "Introduction to Statistics in R", May, 2016
- 10 Linux & CRG Cluster Usage
Advanced linux course for biologists and genomics data formats
Two three-hour sessions to understand some of the main genomics data formats (fasta, fastq, gtf, bed...) and to learn how to parse them. Course material available here.
CRG course: Introduction to R and exploratory data analysis - February/March 2019
The eight three and a half-hour hands-on sessions of how to use R-Studio, learn and practice the basics in R, perform plotting and exploratory data analysis. Course material:
here
Introduction to containers - December 2018 and January 2019
[[file:|300px]]
The two four-hour hands-on sessions of how to create and use containers (Docker and Singularity).
Course material:
here
CRG course: Introduction to R - March/April 2018
The four four-hour hands-on sessions of how to use R-Studio, learn and practice the basics in R, and perform basic plotting and data analysis. For more information, course materials, and links to external teaching resources, visit the course page.
CRG PhD Course 2017-2018 "Introduction to Statistics in R"
The three two-hour hands-on sessions of how to use R-Studio and perform basic plotting and data analysis. For more information, course materials, and links to external teaching resources, visit the course page.
CRG course "Introduction to R"
12h very slow paced hands-on to learn how to use R. For more information, course materials, and links to external teaching resources,
visit the course website.
CRG course "Introduction to Statistics and R programming", May - June, 2017
In this course, the introduction to R is offered in 4 slow-paced practicums for absolute beginners, followed by 3 fast-paced practicums of statistical modules. The statistics material is offered in 3 consecutive modules, each containing a morning lecture and an afternoon practicum in a computer class.
For more information, course materials, and links to external teaching resources, visit the course page.
For more information, course materials, and links to external teaching resources, visit the course page.
CRG PhD/Master course 2016-2017 "Introduction to Statistics in R"
The hands-on sessions of how to use R-Studio and perform basic plotting and data analysis. For more information, course materials, and links to external teaching resources, visit the course page.
BIST Course "Introduction to Statistics in R", May, 2016
This introductory course to Statistics and Probability theory was modeled after the university-level course Statistics 101.
For more information, course materials, and links to external teaching resources, visit the course website.
For more information, course materials, and links to external teaching resources, visit the course website.
Linux & CRG Cluster Usage
The courses on basic Linux and how to use the CRG cluster are regularly run by the CRG SIT Unit and can be found at the SIT website (accessible only from CRG network).