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⏱ 2h 48m📚 28 lessons🎧 Audio version
Text Processing on the Command Line for Data Science
Learn to inspect, filter, and transform data files using powerful terminal tools and pipelines.
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About this course
Data professionals often spend hours cleaning and exploring raw data files before they even begin analysis. Performing these tasks directly in the terminal saves time, bypasses memory limitations, and automates repetitive workflows. This course teaches you how to leverage the command line to inspect, clean, and manipulate text data quickly and efficiently. You will transition from manual file inspection to writing powerful, automated text-processing pipelines. What you'll learn: Understand foundational terminal concepts, command structures, and how to read system documentation; Inspect large data files efficiently using commands like head, tail, and less without loading them into memory; Filter and search text patterns using regular expressions with grep and modern search tools; Transform and clean text data using stream editors and text-processing utilities like sed and awk; Combine multiple commands using redirection and pipes to build powerful automated data pipelines; Process modern structured data formats like JSON and CSV directly from the command line. You will start with the basic mechanics of the command-line interface, learning how to navigate files and access help. Then, you will progress to practical text manipulation, regular expressions, and building multi-stage pipelines to prepare data for analysis. This course is designed for aspiring data analysts, data scientists, and developers who want to work faster with data files, with no prior command-line experience required. Master the terminal tools that will supercharge your data preparation workflow today.
Course contents
What you'll get
📜Certificate of completion Add it to your LinkedIn profile
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⚡Short & focused 2h 48m of practical content
Certificate of completion
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Text Processing on the Command Line for Data Science
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Text Processing on the Command Line for Data Science