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Big Data with PySpark

Master how to process big data and leverage it efficiently with Apache Spark using the PySpark API.
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PythonImporting & Cleaning Data25 hours

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Track Description

Big Data with PySpark

Advance your data skills by mastering Apache Spark. Using the Spark Python API, PySpark, you will leverage parallel computation with large datasets, and get ready for high-performance machine learning. From cleaning data to creating features and implementing machine learning models, you'll execute end-to-end workflows with Spark. The track ends with building a recommendation engine using the popular MovieLens dataset and the Million Songs dataset.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to PySpark

    Master PySpark to handle big data with ease—learn to process, query, and optimize massive datasets for powerful analytics!

  • Course

    5

    Feature Engineering with PySpark

    Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

  • Course

    6

    Machine Learning with PySpark

    Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

  • Project

    bonus

    Building a Demand Forecasting Model

    Use PySpark to build an e-commerce forecasting model!

Big Data with PySpark
6 Courses
Track
Complete

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