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Linux for Data Engineers (Hands On)
Role Play
Rating: 4.2 out of 5(198 ratings)
31,807 students

Linux for Data Engineers (Hands On)

Learn everything about Linux for Data Engineers (Hands On) for beginners
Last updated 5/2026
English

What you'll learn

  • Understand Linux distributions and why Linux is important for data engineers.
  • Install Ubuntu Desktop on your machine (step-by-step, including Windows 10 setup).
  • Explore the Linux file system structure and navigate effectively.
  • Perform basic Linux operations (files, directories, users, processes).
  • Work with system log files such as /var/log to monitor and troubleshoot.
  • Learn and use file permissions (chmod) to secure files.
  • Practice with Linux editors (nano and vi) to edit files and configurations.
  • Master keyboard shortcuts to increase productivity.
  • Write bash shell scripts to automate repetitive tasks.
  • Work with functions, parameters, loops, and conditional statements in scripts.
  • Understand interactive shell scripting for real-world automation.
  • Apply scripting knowledge to tasks like parsing logs, scheduling jobs, and managing data.

Course content

3 sections39 lectures1h 49m total length
  • Introduction4:47

    Explore practical Linux for data engineers through hands-on sessions that cover essential Linux commands, shell scripting, data manipulation, and introductory Ubuntu setup, preparing you for big data workflows.

  • Introduction to Linux1:26
  • Linux Distributions3:11

Requirements

  • No prior Linux knowledge required – we start from the basics.
  • A computer (Windows, macOS, or Linux) with internet connection.
  • Ability to install Ubuntu Desktop (we will guide you step by step).
  • Basic understanding of data engineering concepts is helpful but not mandatory.
  • Willingness to practice Linux commands and scripting for a hands-on learning experience.

Description

Are you a data engineer, data analyst, or big data enthusiast who wants to build a strong foundation in Linux?
If yes, then this course – Linux for Data Engineers (Hands-On) – is designed specifically for you.


Linux is the backbone of modern data engineering and big data systems. Most of the tools in the Hadoop and Spark ecosystem run on Linux-based servers. As a data engineer, being comfortable with Linux commands, file systems, permissions, and shell scripting is not optional – it’s essential.


In this course, you will go from Linux basics to advanced shell scripting, with a focus on practical, hands-on learning. You will not only learn the commands but also understand how to use them in real-world data engineering scenarios such as working with log files, automating workflows, and managing data pipelines.


By the end of the course, you will have the Linux skills every data engineer needs to succeed in real-world big data projects.


What You’ll Learn


  • Understand Linux distributions and why Linux is important for data engineers.

  • Install Ubuntu Desktop on your machine (step-by-step, including Windows 10 setup).

  • Explore the Linux file system structure and navigate effectively.

  • Perform basic Linux operations (files, directories, users, processes).

  • Work with system log files such as /var/log to monitor and troubleshoot.

  • Learn and use file permissions (chmod) to secure files.

  • Practice with Linux editors (nano and vi) to edit files and configurations.

  • Master keyboard shortcuts to increase productivity.

  • Write bash shell scripts to automate repetitive tasks.

  • Work with functions, parameters, loops, and conditional statements in scripts.

  • Understand interactive shell scripting for real-world automation.

  • Apply scripting knowledge to tasks like parsing logs, scheduling jobs, and managing data.

Who this course is for:

  • Data Engineers & Big Data Developers who need Linux for Hadoop, Spark, and other ecosystem tools.
  • SQL Developers or Analysts transitioning into data engineering roles.
  • Beginners in Linux who want a structured, hands-on introduction.
  • Students and Professionals who want to build a career in data engineering, big data, or cloud technologies.