Data Science Productivity Tools from Harvard
| Learning Experience | 9.7 |
|---|
Keep your projects organized and produce reproducible reports using Data Science Productivity Tools from GitHub, git, Unix/Linux, and R Studio.
Introduction
Keep your projects organized and produce reproducible reports using Data Science Productivity Tools from GitHub, git, Unix/Linux, and R Studio.
About this course
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. Introduction of 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 R Studio.
What you will learn from Data Science: Productivity Tools?
- How to use Unix/Linux to manage your file system.
- How to perform version control with git.
- Starting a repository on GitHub.
- To leverage the many useful features provided by R Studio.
Syllabus
1. Introduction and Welcome
2. Section 1: Installing Software,
3. Section 2: Basic Unix
4. Section 3: Reproducible Reports
5. Section 4: Git and GitHub
6. Section 5: Advanced Unix
Note: Your review matters
If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.
FAQ
Description
Introduction
Keep your projects organized and produce reproducible reports using Data Science Productivity Tools from GitHub, git, Unix/Linux, and R Studio.
About this course
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. Introduction of 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 R Studio.
What you will learn from Data Science: Productivity Tools?
- How to use Unix/Linux to manage your file system.
- How to perform version control with git.
- Starting a repository on GitHub.
- To leverage the many useful features provided by R Studio.
Syllabus
1. Introduction and Welcome
2. Section 1: Installing Software,
3. Section 2: Basic Unix
4. Section 3: Reproducible Reports
5. Section 4: Git and GitHub
6. Section 5: Advanced Unix
Note: Your review matters
If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.
FAQ
Specification:
- EDX
- Harvard University
- Online Course
- Self-paced
- Beginner
- 1-3 Months
- Free Course (Affordable Certificate)
- English
- R
- Git RStudio
- None Pre-requisite
- Data Science Data Science with 'R' GitHub Practical Statistics
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