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HarvardX: Data Science: Productivity Tools

4.3 stars
34 ratings

Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio.

Data Science: Productivity Tools
8 semanas
1–2 horas por semana
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Comienza el 21 nov
Termina el 18 dic
Comienza el 21 nov
Comienza el 16 abr 2025

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A typical data analysis project may involve several parts, each including several data files and different scripts with code. Keeping all this organized can be challenging.

Part of our Professional Certificate Program in Data Science, this course explains how to use Unix/Linux as a tool for managing files and directories on your computer and how to keep the file system organized. You will be introduced to the version control systems git, a powerful tool for keeping track of changes in your scripts and reports. We also introduce you to GitHub and demonstrate how you can use this service to keep your work in a repository that facilitates collaborations.

Finally, you will learn to write reports in R markdown which permits you to incorporate text and code into a document. We'll put it all together using the powerful integrated desktop environment RStudio.

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  • Language English
  • Video Transcript English
  • Associated programs
  • Associated skillsData Analysis, Report Writing, Github, Git (Version Control System), Version Control, Markdown, Productivity Software, Rmarkdown, Linux, Data Science, File Systems, R (Programming Language), Unix

Lo que aprenderás

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  • How to use Unix/Linux to manage your file system
  • How to perform version control with git
  • How to start a repository on GitHub
  • How to leverage the many useful features provided by RStudio

Preguntas frecuentes

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Honor code statement
HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

Research statement
By registering as an online learner in our open online courses, you are also participating in research intended to enhance HarvardX's instructional offerings as well as the quality of learning and related sciences worldwide. In the interest of research, you may be exposed to some variations in the course materials. HarvardX does not use learner data for any purpose beyond the University's stated missions of education and research. For purposes of research, we may share information we collect from online learning activities, including Personally Identifiable Information, with researchers beyond Harvard. However, your Personally Identifiable Information will only be shared as permitted by applicable law, will be limited to what is necessary to perform the research, and will be subject to an agreement to protect the data. We may also share with the public or third parties aggregated information that does not personally identify you. Similarly, any research findings will be reported at the aggregate level and will not expose your personal identity.

Please read the edX Privacy Policy for more information regarding the processing, transmission, and use of data collected through the edX platform.

Nondiscrimination/anti-harassment statement
Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

Este curso es parte del programa Data Science Professional Certificate

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Instrucción por expertos
9 cursos de capacitación
A tu ritmo
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1 año 5 meses
2 - 3 horas semanales

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