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Automation and Make
Unrestricted Use
CC BY
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A Software Carpentry lesson to learn how to use Make Make is a tool which can run commands to read files, process these files in some way, and write out the processed files. For example, in software development, Make is used to compile source code into executable programs or libraries, but Make can also be used to: run analysis scripts on raw data files to get data files that summarize the raw data; run visualization scripts on data files to produce plots; and to parse and combine text files and plots to create papers. Make is called a build tool - it builds data files, plots, papers, programs or libraries. It can also update existing files if desired. Make tracks the dependencies between the files it creates and the files used to create these. If one of the original files (e.g. a data file) is changed, then Make knows to recreate, or update, the files that depend upon this file (e.g. a plot). There are now many build tools available, all of which are based on the same concepts as Make.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Richie-Halford
Ana Costa Conrado
Andrew Boughton
Andrew Fraser
Andy Kleinhesselink
Andy Teucher
Anna Krystalli
Bill Mills
Brandon Curtis
David E. Bernholdt
Deborah Gertrude Digges
François Michonneau
Gerard Capes
Greg Wilson
Jake Lever
Jason Sherman
John Blischak
Jonah Duckles
Juan F Fung
Kate Hertweck
Lex Nederbragt
Luiz Irber
Matthew Thomas
Michael Culshaw-Maurer
Mike Jackson
Pete Bachant
Piotr Banaszkiewicz
Radovan Bast
Raniere Silva
Rémi Emonet
Samuel Lelièvre
Satya Mishra
Trevor Bekolay
Date Added:
03/20/2017
Carpentries Instructor Training
Unrestricted Use
CC BY
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A two-day introduction to modern evidence-based teaching practices, built and maintained by the Carpentry community.

Subject:
Applied Science
Computer Science
Education
Higher Education
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Aleksandra Nenadic
Alexander Konovalov
Alistair John Walsh
Allison Weber
Amy E. Hodge
Andrew B. Collier
Anita Schürch
AnnaWilliford
Ariel Rokem
Brian Ballsun-Stanton
Callin Switzer
Christian Brueffer
Christina Koch
Christopher Erdmann
Colin Morris
Dan Allan
DanielBrett
Danielle Quinn
Darya Vanichkina
David Jennings
Eric Jankowski
Erin Alison Becker
Evan Peter Williamson
François Michonneau
Gerard Capes
Greg Wilson
Ian Lee
Jason M Gates
Jason Williams
Jeffrey Oliver
Joe Atzberger
John Bradley
John Pellman
Jonah Duckles
Jonathan Bradley
Karen Cranston
Karen Word
Kari L Jordan
Katherine Koziar
Katrin Leinweber
Kees den Heijer
Laurence
Lex Nederbragt
Maneesha Sane
Marie-Helene Burle
Mik Black
Mike Henry
Murray Cadzow
Neal Davis
Neil Kindlon
Nicholas Tierney
Nicolás Palopoli
Noah Spies
Paula Andrea Martinez
Petraea
Rayna Michelle Harris
Rémi Emonet
Rémi Rampin
Sarah Brown
Sarah M Brown
Sarah Stevens
Sean
Serah Anne Njambi Kiburu
Stefan Helfrich
Steve Moss
Stéphane Guillou
Ted Laderas
Tiago M. D. Pereira
Toby Hodges
Tracy Teal
Yo Yehudi
amoskane
davidbenncsiro
naught101
satya-vinay
Date Added:
08/07/2020
Databases and SQL
Unrestricted Use
CC BY
Rating
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Software Carpentry lesson that teaches how to use databases and SQL In the late 1920s and early 1930s, William Dyer, Frank Pabodie, and Valentina Roerich led expeditions to the Pole of Inaccessibility in the South Pacific, and then onward to Antarctica. Two years ago, their expeditions were found in a storage locker at Miskatonic University. We have scanned and OCR the data they contain, and we now want to store that information in a way that will make search and analysis easy. Three common options for storage are text files, spreadsheets, and databases. Text files are easiest to create, and work well with version control, but then we would have to build search and analysis tools ourselves. Spreadsheets are good for doing simple analyses, but they don’t handle large or complex data sets well. Databases, however, include powerful tools for search and analysis, and can handle large, complex data sets. These lessons will show how to use a database to explore the expeditions’ data.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Amy Brown
Andrew Boughton
Andrew Kubiak
Avishek Kumar
Ben Waugh
Bill Mills
Brian Ballsun-Stanton
Chris Tomlinson
Colleen Fallaw
Dan Michael Heggø
Daniel Suess
Dave Welch
David W Wright
Deborah Gertrude Digges
Donny Winston
Doug Latornell
Erin Alison Becker
Ethan Nelson
Ethan P White
François Michonneau
George Graham
Gerard Capes
Gideon Juve
Greg Wilson
Ioan Vancea
Jake Lever
James Mickley
John Blischak
JohnRMoreau@gmail.com
Jonah Duckles
Jonathan Guyer
Joshua Nahum
Kate Hertweck
Kevin Dyke
Louis Vernon
Luc Small
Luke William Johnston
Maneesha Sane
Mark Stacy
Matthew Collins
Matty Jones
Mike Jackson
Morgan Taschuk
Patrick McCann
Paula Andrea Martinez
Pauline Barmby
Piotr Banaszkiewicz
Raniere Silva
Ray Bell
Rayna Michelle Harris
Rémi Emonet
Rémi Rampin
Seda Arat
Sheldon John McKay
Sheldon McKay
Stephen Davison
Thomas Guignard
Trevor Bekolay
lorra
slimlime
Date Added:
03/20/2017
El Control de Versiones con Git
Unrestricted Use
CC BY
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Software Carpentry lección para control de versiones con Git Para ilustrar el poder de Git y GitHub, usaremos la siguiente historia como un ejemplo motivador a través de esta lección. El Hombre Lobo y Drácula han sido contratados por Universal Missions para investigar si es posible enviar su próximo explorador planetario a Marte. Ellos quieren poder trabajar al mismo tiempo en los planes, pero ya han experimentado ciertos problemas anteriormente al hacer algo similar. Si se rotan por turnos entonces cada uno gastará mucho tiempo esperando a que el otro termine, pero si trabajan en sus propias copias e intercambian los cambios por email, las cosas se perderán, se sobreescribirán o se duplicarán. Un colega sugiere utilizar control de versiones para lidiar con el trabajo. El control de versiones es mejor que el intercambio de ficheros por email: Nada se pierde una vez que se incluye bajo control de versiones, a no ser que se haga un esfuerzo sustancial. Como se van guardando todas las versiones precedentes de los ficheros, siempre es posible volver atrás en el tiempo y ver exactamente quién escribió qué en un día en particular, o qué versión de un programa fue utilizada para generar un conjunto de resultados en particular. Como se tienen estos registros de quién hizo qué y en qué momento, es posible saber a quién preguntar si se tiene una pregunta en un momento posterior y, si es necesario, revertir el contenido a una versión anterior, de forma similar a como funciona el comando “deshacer” de los editores de texto. Cuando varias personas colaboran en el mismo proyecto, es posible pasar por alto o sobreescribir de manera accidental los cambios hechos por otra persona. El sistema de control de versiones notifica automáticamente a los usuarios cada vez que hay un conflicto entre el trabajo de una persona y la otra. Los equipos no son los únicos que se benefician del control de versiones: los investigadores independientes se pueden beneficiar en gran medida. Mantener un registro de qué ha cambiado, cuándo y por qué es extremadamente útil para todos los investigadores si alguna vez necesitan retomar el proyecto en un momento posterior (e.g. un año después, cuando se ha desvanecido el recuerdo de los detalles).

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Alejandra Gonzalez-Beltran
Amy Olex
Belinda Weaver
Bradford Condon
Casey Youngflesh
Daisie Huang
Dani Ledezma
Francisco Palm
Garrett Bachant
Heather Nunn
Hely Salgado
Ian Lee
Ivan Gonzalez
James E McClure
Javier Forment
Jimmy O'Donnell
Jonah Duckles
K.E. Koziar
Katherine Koziar
Katrin Leinweber
Kevin Alquicira
Kevin MF
Kurt Glaesemann
LauCIFASIS
Leticia Vega
Lex Nederbragt
Mark Woodbridge
Matias Andina
Matt Critchlow
Mingsheng Zhang
Nelly Sélem
Nima Hejazi
Nohemi Huanca Nunez
Olemis Lang
P. L. Lim
Paula Andrea Martinez
Peace Ossom Williamson
Rayna M Harris
Romualdo Zayas-Lagunas
Sarah Stevens
Saskia Hiltemann
Shirley Alquicira
Silvana Pereyra
Tom Morrell
Valentina Bonetti
Veronica Ikeshoji-Orlati
Veronica Jimenez
butterflyskip
dounia
Date Added:
08/07/2020
La Terminal de Unix
Unrestricted Use
CC BY
Rating
0.0 stars

Software Carpentry lección para la terminal de Unix La terminal de Unix ha existido por más tiempo que la mayoría de sus usuarios. Ha sobrevivido tanto tiempo porque es una herramienta poderosa que permite a las personas hacer cosas complejas con sólo unas pocas teclas. Lo más importante es que ayuda a combinar programas existentes de nuevas maneras y automatizar tareas repetitivas, en vez de estar escribiendo las mismas cosas una y otra vez. El uso del terminal o shell es fundamental para usar muchas otras herramientas poderosas y recursos informáticos (incluidos los supercomputadores o “computación de alto rendimiento”). Esta lección te guiará en el camino hacia el uso eficaz de estos recursos.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Huffman
Alejandra Gonzalez-Beltran
AnaBVA
Andrew Sanchez
Anja Le Blanc
Ashwin Srinath
Brian Ballsun-Stanton
Colin Morris
Dani Ledezma
Dave Bridges
Erin Becker
Francisco Palm
François Michonneau
Gabriel A. Devenyi
Gerard Capes
Giuseppe Profiti
Gordon Rhea
Jake Cowper Szamosi
Jared Flater
Jeff Oliver
Jonah Duckles
Juan M. Barrios
Katrin Leinweber
Kelly L. Rowland
Kevin Alquicira
Kunal Marwaha
LauCIFASIS
Marisa Lim
Martha Robinson
Matias Andina
Michael Zingale
Nicolas Barral
Nohemi Huanca Nunez
Olemis Lang
Otoniel Maya
Paula Andrea Martinez
Raniere Silva
Rayna M Harris
Shirley Alquicira
Silvana Pereyra
Steve Leak
Stéphane Guillou
Thomas Mellan
Veronica Jimenez-Jacinto
William L. Close
Yee Mey
csqrs
sjnair
Date Added:
08/07/2020
Library Carpentry: Introduction to Git
Unrestricted Use
CC BY
Rating
0.0 stars

Library Carpentry lesson: An introduction to Git. What We Will Try to Do Begin to understand and use Git/GitHub. You will not be an expert by the end of the class. You will probably not even feel very comfortable using Git. This is okay. We want to make a start but, as with any skill, using Git takes practice. Be Excellent to Each Other If you spot someone in the class who is struggling with something and you think you know how to help, please give them a hand. Try not to do the task for them: instead explain the steps they need to take and what these steps will achieve. Be Patient With The Instructor and Yourself This is a big group, with different levels of knowledge, different computer systems. This isn’t your instructor’s full-time job (though if someone wants to pay them to play with computers all day they’d probably accept). They will do their best to make this session useful. This is your session. If you feel we are going too fast, then please put up a pink sticky. We can decide as a group what to cover.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
222064h
Alex Mendes
Alexander Gary Zimmerman
Alexander Mendes
Amiya Maji
Amy Olex
Andrew Lonsdale
Annika Rockenberger
Begüm D. Topçuoğlu
Belinda Weaver
Benjamin Bolker
Bill McMillin
Brian Moore
Casey Youngflesh
Christoph Junghans
Christopher Erdmann
DSTraining
Dan Michael O. Heggø
David Jennings
Erin Alison Becker
Evan Williamson
Garrett Bachant
Grant Sayer
Ian Lee
Jake Lever
Jamene Brooks-Kieffer
James Baker
James E McClure
James O'Donnell
James Tocknell
Janoš Vidali
Jeffrey Oliver
Jeremy Teitelbaum
Jeyashree Krishnan
Joe Atzberger
Jonah Duckles
Jonathan Cooper
João Rodrigues
Katherine Koziar
Katrin Leinweber
Kunal Marwaha
Kurt Glaesemann
L.C. Karssen
Lauren Ko
Lex Nederbragt
Madicken Munk
Maneesha Sane
Marie-Helene Burle
Mark Woodbridge
Martino Sorbaro
Matt Critchlow
Matteo Ceschia
Matthew Bourque
Matthew Hartley
Maxim Belkin
Megan Potterbusch
Michael Torpey
Michael Zingale
Mingsheng Zhang
Nicola Soranzo
Nima Hejazi
Nora McGregor
Oscar Arbeláez
Peace Ossom Williamson
Raniere Silva
Rayna Harris
Rene Gassmoeller
Rich McCue
Richard Barnes
Ruud Steltenpool
Ryan Wick
Rémi Emonet
Samniqueka Halsey
Samuel Lelièvre
Sarah Stevens
Saskia Hiltemann
Schlauch, Tobias
Scott Bailey
Shari Laster
Simon Waldman
Stefan Siegert
Thea Atwood
Thomas Morrell
Tim Dennis
Tommy Keswick
Tracy Teal
Trevor Keller
TrevorLeeCline
Tyler Crawford Kelly
Tyler Reddy
Umihiko Hoshijima
Veronica Ikeshoji-Orlati
Wes Harrell
Will Usher
William Sacks
Wolmar Nyberg Åkerström
Yuri
abracarambar
ajtag
butterflyskip
cmjt
hdinkel
jonestoddcm
pllim
Date Added:
08/07/2020
Library Carpentry: Introduction to Working with Data (Regular Expressions)
Unrestricted Use
CC BY
Rating
0.0 stars

This Library Carpentry lesson introduces librarians and others to working with data. This Library Carpentry lesson introduces people with library- and information-related roles to working with data using regular expressions. The lesson provides background on the regular expression language and how it can be used to match and extract text and to clean data.

Subject:
Applied Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Alex Volkov
Alexander Mendes
Angus Taggart
Belinda Weaver
BertrandCaron
Bianca Peterson
Christopher Edsall
Christopher Erdmann
Chuck McAndrew
Dan Michael Heggø
Dan Michael O. Heggø
Elizabeth Lisa McAulay
Felix Hemme
François Michonneau
James Baker
Janice Chan
Jeffrey Oliver
Jeremy Guillette
Jodi Schneider
Jonah Duckles
Katherine Koziar
Katrin Leinweber
Kunal Marwaha
PH03N1X007
Paul R. Pival
Saskia Scheltjens
Shari Laster
Tim Dennis
fdsayre
lsult
remerjohnson
yvonnemery
Date Added:
08/07/2020
Library Carpentry: The UNIX Shell
Unrestricted Use
CC BY
Rating
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Library Carpentry lesson to learn how to use the Shell. This Library Carpentry lesson introduces librarians to the Unix Shell. At the conclusion of the lesson you will: understand the basics of the Unix shell; understand why and how to use the command line; use shell commands to work with directories and files; use shell commands to find and manipulate data.

Subject:
Applied Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Huffman
Alex Kassil
Alex Mendes
Alexander Konovalov
Alexander Morley
Ana Costa Conrado
Andrew Reid
Andrew T. T. McRae
Ariel Rokem
Ashwin Srinath
Bagus Tris Atmaja
Belinda Weaver
Benjamin Bolker
Benjamin Gabriel
BertrandCaron
Brian Ballsun-Stanton
Christopher Erdmann
Christopher Mentzel
Colin Sauze
Dan Michael Heggø
Dave Bridges
David McKain
Dmytro Lituiev
Elena Denisenko
Eric Jankowski
Erin Alison Becker
Evan Williamson
Farah Shamma
Gabriel Devenyi
Gerard Capes
Giuseppe Profiti
Halle Burns
Hannah Burkhardt
Ian Lessing
Ian van der Linde
Jake Cowper Szamosi
James Baker
James Guelfi
Jarno Rantaharju
Jarosław Bryk
Jason Macklin
Jeffrey Oliver
John Pellman
Jonah Duckles
Jonny Williams
Katrin Leinweber
Kevin M. Buckley
Kunal Marwaha
Laurence
Marc Gouw
Marie-Helene Burle
Marisa Lim
Martha Robinson
Martin Feller
Megan Fritz
Michael Lascarides
Michael Zingale
Michele Hayslett
Mike Henry
Morgan Oneka
Murray Hoggett
Nicola Soranzo
Nicolas Barral
Noah D Brenowitz
Owen Kaluza
Patrick McCann
Peter Hoyt
Rafi Ullah
Raniere Silva
Ruud Steltenpool
Rémi Emonet
Stephan Schmeing
Stephen Jones
Stephen Leak
Stéphane Guillou
Susan J Miller
Thomas Mellan
Tim Dennis
Tom Dowrick
Travis Lilleberg
Victor Koppejan
Vikram Chhatre
Yee Mey
colinmorris
csqrs
earkpr
ekaterinailin
hugolio
jenniferleeucalgary
reshama shaikh
sjnair
Date Added:
08/07/2020
Plotting and Programming in Python
Unrestricted Use
CC BY
Rating
0.0 stars

This lesson is part of Software Carpentry workshops and teach an introduction to plotting and programming using python. This lesson is an introduction to programming in Python for people with little or no previous programming experience. It uses plotting as its motivating example, and is designed to be used in both Data Carpentry and Software Carpentry workshops. This lesson references JupyterLab, but can be taught using a regular Python interpreter as well. Please note that this lesson uses Python 3 rather than Python 2.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Steer
Allen Lee
Andreas Hilboll
Ashley Champagne
Benjamin
Benjamin Roberts
CanWood
Carlos Henrique Brandt
Carlos M Ortiz Marrero
Cephalopd
Cian Wilson
Dan Mønster
Daniel W Kerchner
Daria Orlowska
Dave Lampert
David Matten
Erin Alison Becker
Florian Goth
Francisco J. Martínez
Greg Wilson
Jacob Deppen
Jarno Rantaharju
Jeremy Zucker
Jonah Duckles
Kees den Heijer
Keith Gilbertson
Kyle E Niemeyer
Lex Nederbragt
Logan Cox
Louis Vernon
Lucy Dorothy Whalley
Madeleine Bonsma-Fisher
Mark Phillips
Mark Slater
Maxim Belkin
Michael Beyeler
Mike Henry
Narayanan Raghupathy
Nigel Bosch
Olav Vahtras
Pablo Hernandez-Cerdan
Paul Anzel
Phil Tooley
Raniere Silva
Robert Woodward
Ryan Avery
Ryan Gregory James
SBolo
Sarah M Brown
Shyam Dwaraknath
Sourav Singh
Steven Koenig
Stéphane Guillou
Taylor Smith
Thor Wikfeldt
Timothy Warren
Tyler Martin
Vasu Venkateshwaran
Vikas Pejaver
ian
mzc9
Date Added:
08/07/2020
R for Reproducible Scientific Analysis
Unrestricted Use
CC BY
Rating
0.0 stars

This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam H. Sparks
Ahsan Ali Khoja
Amy Lee
Ana Costa Conrado
Andrew Boughton
Andrew Lonsdale
Andrew MacDonald
Andris Jankevics
Andy Teucher
Antonio Berlanga-Taylor
Ashwin Srinath
Ben Bolker
Bill Mills
Bret Beheim
Clare Sloggett
Daniel
Dave Bridges
David J. Harris
David Mawdsley
Dean Attali
Diego Rabatone Oliveira
Drew Tyre
Elise Morrison
Erin Alison Becker
Fernando Mayer
François Michonneau
Giulio Valentino Dalla Riva
Gordon McDonald
Greg Wilson
Harriet Dashnow
Ido Bar
Jaime Ashander
James Balamuta
James Mickley
Jamie McDevitt-Irwin
Jeffrey Arnold
Jeffrey Oliver
John Blischak
Jonah Duckles
Josh Quan
Julia Piaskowski
Kara Woo
Kate Hertweck
Katherine Koziar
Katrin Leinweber
Kellie Ottoboni
Kevin Weitemier
Kiana Ashley West
Kieran Samuk
Kunal Marwaha
Kyriakos Chatzidimitriou
Lachlan Deer
Lex Nederbragt
Liz Ing-Simmons
Lucy Chang
Luke W Johnston
Luke Zappia
Marc Sze
Marie-Helene Burle
Marieke Frassl
Mark Dunning
Martin John Hadley
Mary Donovan
Matt Clark
Melissa Kardish
Mike Jackson
Murray Cadzow
Narayanan Raghupathy
Naupaka Zimmerman
Nelly Sélem
Nicholas Lesniak
Nicholas Potter
Nima Hejazi
Nora Mitchell
Olivia Rata Burge
Paula Andrea Martinez
Pete Bachant
Phil Bouchet
Philipp Boersch-Supan
Piotr Banaszkiewicz
Raniere Silva
Rayna Michelle Harris
Remi Daigle
Research Bazaar
Richard Barnes
Robert Bagchi
Rémi Emonet
Sam Penrose
Sandra Brosda
Sarah Munro
Sasha Lavrentovich
Scott Allen Funkhouser
Scott Ritchie
Sebastien Renaut
Thea Van Rossum
Timothy Eoin Moore
Timothy Rice
Tobin Magle
Trevor Bekolay
Tyler Crawford Kelly
Vicken Hillis
Yuka Takemon
bippuspm
butterflyskip
waiteb5
Date Added:
03/20/2017
R para Análisis Científicos Reproducibles
Unrestricted Use
CC BY
Rating
0.0 stars

Una introducción a R utilizando los datos de Gapminder. El objetivo de esta lección es enseñar a las programadoras principiantes a escribir códigos modulares y adoptar buenas prácticas en el uso de R para el análisis de datos. R nos provee un conjunto de paquetes desarrollados por terceros que se usan comúnmente en diversas disciplinas científicas para el análisis estadístico. Encontramos que muchos científicos que asisten a los talleres de Software Carpentry utilizan R y quieren aprender más. Nuestros materiales son relevantes ya que proporcionan a los asistentes una base sólida en los fundamentos de R y enseñan las mejores prácticas del cómputo científico: desglose del análisis en módulos, automatización tareas y encapsulamiento. Ten en cuenta que este taller se enfoca en los fundamentos del lenguaje de programación R y no en el análisis estadístico. A lo largo de este taller se utilizan una variedad de paquetes desarrolados por terceros, los cuales no son necesariamente los mejores ni se encuentran explicadas todas sus funcionalidades, pero son paquetes que consideramos útiles y han sido elegidos principalmente por su facilidad de uso.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
0xgc
A. s
Alejandra Gonzalez-Beltran
Ana Beatriz Villaseñor Altamirano
Antonio
AntonioJBT
Belinda Weaver
Claudia Engel
Cynthia Monastirsky
Daniel Beiter
David Mawdsley
David Pérez-Suárez
Erin Becker
EuniceML
François Michonneau
Gordon McDonald
Guillermina Actis
Guillermo Movia
Hely Salgado
Ido Bar
Ivan Ogasawara
Ivonne Lujano
James J Balamuta
Jamie McDevitt-Irwin
Jeff Oliver
Jonah Duckles
Juan M. Barrios
Katrin Leinweber
Kevin Alquicira
Kevin Martínez-Folgar
Laura Angelone
Laura-Gomez
Leticia Vega
Marcela Alfaro Córdoba
Marceline Abadeer
Maria Florencia D'Andrea
Marie-Helene Burle
Marieke Frassl
Matias Andina
Murray Cadzow
Narayanan Raghupathy
Naupaka Zimmerman
Paola Prieto
Paula Andrea Martinez
Raniere Silva
Rayna M Harris
Richard Barnes
Richard McCosh
Romualdo Zayas-Lagunas
Sandra Brosda
Sasha Lavrentovich
Shirley Alquicira Hernandez
Silvana Pereyra
Tobin Magle
Veronica Jimenez
juli arancio
raynamharris
saynomoregrl
Date Added:
08/07/2020
The Unix Shell
Unrestricted Use
CC BY
Rating
0.0 stars

Software Carpentry lesson on how to use the shell to navigate the filesystem and write simple loops and scripts. The Unix shell has been around longer than most of its users have been alive. It has survived so long because it’s a power tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren’t typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources (including “high-performance computing” supercomputers). These lessons will start you on a path towards using these resources effectively.

Subject:
Applied Science
Computer Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Huffman
Adam James Orr
Adam Richie-Halford
AidaMirsalehi
Alex Kassil
Alex Mac
Alexander Konovalov
Alexander Morley
Alix Keener
Amy Brown
Andrea Bedini
Andrew Boughton
Andrew Reid
Andrew T. T. McRae
Andrew Walker
Ariel Rokem
Armin Sobhani
Ashwin Srinath
Bagus Tris Atmaja
Bartosz Telenczuk
Ben Bolker
Benjamin Gabriel
Bertie Seyffert
Bill Mills
Brian Ballsun-Stanton
BrianBill
Camille Marini
Chris Mentzel
Christina Koch
Colin Morris
Colin Sauze
Damien Irving
Dan Jones
Dana Brunson
Daniel Baird
Daniel McCloy
Daniel Standage
Danielle M. Nielsen
Dave Bridges
David Eyers
David McKain
David Vollmer
Dean Attali
Devinsuit
Dmytro Lituiev
Donny Winston
Doug Latornell
Dustin Lang
Elena Denisenko
Emily Dolson
Emily Jane McTavish
Eric Jankowski
Erin Alison Becker
Ethan P White
Evgenij Belikov
Farah Shamma
Fatma Deniz
Filipe Fernandes
Francis Gacenga
François Michonneau
Gabriel A. Devenyi
Gerard Capes
Giuseppe Profiti
Greg Wilson
Halle Burns
Hannah Burkhardt
Harriet Alexander
Hugues Fontenelle
Ian van der Linde
Inigo Aldazabal Mensa
Jackie Milhans
Jake Cowper Szamosi
James Guelfi
Jan T. Kim
Jarek Bryk
Jarno Rantaharju
Jason Macklin
Jay van Schyndel
Jens vdL
John Blischak
John Pellman
John Simpson
Jonah Duckles
Jonny Williams
Joshua Madin
Kai Blin
Kathy Chung
Katrin Leinweber
Kevin M. Buckley
Kirill Palamartchouk
Klemens Noga
Kristopher Keipert
Kunal Marwaha
Laurence
Lee Zamparo
Lex Nederbragt
M Carlise
Mahdi Sadjadi
Marc Rajeev Gouw
Marcel Stimberg
Maria Doyle
Marie-Helene Burle
Marisa Lim
Mark Mandel
Martha Robinson
Martin Feller
Matthew Gidden
Matthew Peterson
Megan Fritz
Michael Zingale
Mike Henry
Mike Jackson
Morgan Oneka
Murray Hoggett
Nicola Soranzo
Nicolas Barral
Noah D Brenowitz
Noam Ross
Norman Gray
Orion Buske
Owen Kaluza
Patrick McCann
Paul Gardner
Pauline Barmby
Peter R. Hoyt
Peter Steinbach
Philip Lijnzaad
Phillip Doehle
Piotr Banaszkiewicz
Rafi Ullah
Raniere Silva
Robert A Beagrie
Ruud Steltenpool
Ry4an Brase
Rémi Emonet
Sarah Mount
Sarah Simpkin
Scott Ritchie
Stephan Schmeing
Stephen Jones
Stephen Turner
Steve Leak
Stéphane Guillou
Susan Miller
Thomas Mellan
Tim Keighley
Tobin Magle
Tom Dowrick
Trevor Bekolay
Varda F. Hagh
Victor Koppejan
Vikram Chhatre
Yee Mey
csqrs
earkpr
ekaterinailin
nther
reshama shaikh
s-boardman
sjnair
Date Added:
03/20/2017
Version Control with Git
Unrestricted Use
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This lesson is part of the Software Carpentry workshops that teach how to use version control with Git. Wolfman and Dracula have been hired by Universal Missions (a space services spinoff from Euphoric State University) to investigate if it is possible to send their next planetary lander to Mars. They want to be able to work on the plans at the same time, but they have run into problems doing this in the past. If they take turns, each one will spend a lot of time waiting for the other to finish, but if they work on their own copies and email changes back and forth things will be lost, overwritten, or duplicated. A colleague suggests using version control to manage their work. Version control is better than mailing files back and forth: Nothing that is committed to version control is ever lost, unless you work really, really hard at it. Since all old versions of files are saved, it’s always possible to go back in time to see exactly who wrote what on a particular day, or what version of a program was used to generate a particular set of results. As we have this record of who made what changes when, we know who to ask if we have questions later on, and, if needed, revert to a previous version, much like the “undo” feature in an editor. When several people collaborate in the same project, it’s possible to accidentally overlook or overwrite someone’s changes. The version control system automatically notifies users whenever there’s a conflict between one person’s work and another’s. Teams are not the only ones to benefit from version control: lone researchers can benefit immensely. Keeping a record of what was changed, when, and why is extremely useful for all researchers if they ever need to come back to the project later on (e.g., a year later, when memory has faded). Version control is the lab notebook of the digital world: it’s what professionals use to keep track of what they’ve done and to collaborate with other people. Every large software development project relies on it, and most programmers use it for their small jobs as well. And it isn’t just for software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Alexander G. Zimmerman
Amiya Maji
Amy L Olex
Andrew Lonsdale
Annika Rockenberger
Begüm D. Topçuoğlu
Ben Bolker
Bill Sacks
Brian Moore
Casey Youngflesh
Charlotte Moragh Jones-Todd
Christoph Junghans
David Jennings
Erin Alison Becker
François Michonneau
Garrett Bachant
Grant Sayer
Holger Dinkel
Ian Lee
Jake Lever
James E McClure
James Tocknell
Janoš Vidali
Jeremy Teitelbaum
Jeyashree Krishnan
Jimmy O'Donnell
Joe Atzberger
Jonah Duckles
Jonathan Cooper
João Rodrigues
Katherine Koziar
Katrin Leinweber
Kunal Marwaha
Kurt Glaesemann
L.C. Karssen
Lauren Ko
Lex Nederbragt
Madicken Munk
Maneesha Sane
Marie-Helene Burle
Mark Woodbridge
Martino Sorbaro
Matt Critchlow
Matteo Ceschia
Matthew Bourque
Matthew Hartley
Maxim Belkin
Megan Potterbusch
Michael Torpey
Michael Zingale
Mingsheng Zhang
Nicola Soranzo
Nima Hejazi
Oscar Arbeláez
Peace Ossom Williamson
Pey Lian Lim
Raniere Silva
Rayna Michelle Harris
Rene Gassmoeller
Rich McCue
Richard Barnes
Ruud Steltenpool
Rémi Emonet
Samniqueka Halsey
Samuel Lelièvre
Sarah Stevens
Saskia Hiltemann
Schlauch, Tobias
Scott Bailey
Simon Waldman
Stefan Siegert
Thomas Morrell
Tommy Keswick
Traci P
Tracy Teal
Trevor Keller
TrevorLeeCline
Tyler Crawford Kelly
Tyler Reddy
Umihiko Hoshijima
Veronica Ikeshoji-Orlati
Wes Harrell
Will Usher
Wolmar Nyberg Åkerström
abracarambar
butterflyskip
jonestoddcm
Date Added:
03/20/2017