MISSION 383

Introduction to the Command Line

Learning the command line is essential for a professional data analyst or data scientist. The lack of a graphical user interface (GUI) may make the command line intimidating, but it also makes it faster than other approaches for many tasks. That's why it's a critical part of many efficient data science workflows.

In our Introduction To The Command Line lesson, you will learn why using the command line, also called the terminal, is important, and start learning to execute commands in the terminal on UNIX machines to interact with your computer.

You will also learn the structure of the command line and how it is set up as you dig into common data science command-line tasks like checking for text differences between files using the diff command, finding the current date using the date command, and viewing a list of commands already run using the history command.

Along the way, you’ll discover the similarities and differences between the command line interface and the graphical user interface.

If you're using a Windows PC or laptop to do this lesson, don't worry about not having access to a Unix based terminal! You’ll practice your command line skills right on our platform, which has answer checking built-in so you can be sure you've mastered each concept before moving on to the next concept. 

What You'll Learn

  • What the command line is
  • Why the command line is important in the Data Science workflow
  • How to work with the filesystem from the command line
  • What commands are and how to modify their behavior with options
  • How to access command history

Mission Outline

1. What is the Command Line?
2. Why Learn the Command Line?
3. The Prompt
4. The Anatomy of Commands
5. More on Commands
6. Command History
7. Ending Your Session
8. Next Steps
9. Takeaways

Course Info:

Beginner

The median completion time for this course is 4 hours. View details

This course requires a basic subscription. It includes five missions and it is the ninth course in the Data Analyst in Python path and Data Scientist in Python path.

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