Cleaning Data with PySpark

Engineering and Technology

Short Description

Learn how to clean data with Apache Spark in Python.

Long Description

Working with large amounts of data can be challenging, especially when dealing with millions or billions of rows. If you have received data processing code that was written on a laptop and the data is relatively clean, chances are you have been tasked with transitioning a basic data process from prototype to production. However, you may have also encountered real-world datasets that have missing fields, unusual formatting, and significantly larger amounts of data. Even if you are new to this field, our course is designed to help you gain the necessary skills to prepare data processes using Python with Apache Spark. Throughout the course, you will learn important terminology, methods, and best practices that will enable you to create a high-performing, maintainable, and comprehensible data processing platform.

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Course Details

Duration: 4 hours
Difficulty: Intermediate
Format: Short Course
Price: USD39.00
Course Link

DataCamp

DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.

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