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Data Show and Tell: Data Analysis for Fake Job Posts

Learn how to analyze job posts using Python to detect potentially fake listings. This course covers a practical project teaching data analysis, feature engineering, and rule-based classification skills to flag suspicious patterns effectively.

Ed Freitas - Pluralsight course - Data Show and Tell: Data Analysis for Fake Job Posts
by Ed Freitas

What you'll learn

Fake job postings are a growing challenge on online platforms, misleading job seekers and compromising trust. This course, Data Show and Tell: Data Analysis for Fake Job Posts, demonstrates how to tackle this issue using data analysis. You’ll learn how to extract meaningful features from job descriptions, apply rule-based logic to flag suspicious patterns, and visualize results to validate your findings.

By the end of this course, you’ll have built a functional system that identifies potentially fake job posts, showcasing how Python can be used to solve real-world problems and protect users from fraud.

Table of contents

About the author

Ed Freitas - Pluralsight course - Data Show and Tell: Data Analysis for Fake Job Posts
Ed Freitas

Eduardo is a technology enthusiast, software architect and customer success advocate. He's designed enterprise .NET solutions that extract, validate and automate critical business processes such as Accounts Payable and Mailroom solutions. He's a well-known specialist in the Enterprise Content Management market segment, specifically focusing on data capture & extraction and document process automation.

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