Scalable Data Processing in R

Engineering and Technology

Short Description

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

Long Description

This course addresses the challenge faced by R programmers when working with datasets that exceed the available RAM capacity. By default, all variables are stored in memory, which can lead to issues. In this course, you will acquire the necessary tools to process, explore, and analyze data directly from disk. Additionally, you will learn how to implement the split-apply-combine approach and write scalable code using the bigmemory and iotools packages. Throughout the course, you will work with the Federal Housing Finance Agency's publicly available dataset, which documents all mortgages held or securitized by Fannie Mae and Freddie Mac from 2009 to 2015.

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Course Details

Duration: 4 hours
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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