
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.
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Learn to use apt as a packaging manager to install, update, remove, and search software from the terminal, with a hands-on demo of installing nano.
Practice mkdir, rm, and exit as you create and remove directories, clear the screen, and exit the terminal, demonstrated by navigating to /home/bigdata in a hands-on linux data engineering drill.
Explore basic operations of two commands to locate source or binary files, display the present working directory, and perform a practical demonstration of locating Java installations.
Learn basic Linux compression operations by practical demonstration of gzip and zip, creating and decompressing sample files to illustrate common compression workflows.
Learn to build a bash interactive shell script that reads a user’s name and displays it back, using read and echo commands in a practical hands-on example.
Learn how to pass and access script parameters in bash, using $0 for the script name and $1, $2, $3 for the first, second, and subsequent arguments, with practical demonstrations.
Discover how the case statement works with a fruit variable, matching patterns in a case expression and displaying orange when it matches, while executing corresponding commands.
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.