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Spark

Free Course

Master how to work with big data and build machine learning models at scale using Spark!

Related Nanodegree Program

Data Scientist

In collaboration with
  • Insight

About this course

In this course, you’ll learn how to use Spark to work with big data and build machine learning models at scale, including how to wrangle and model massive datasets with PySpark, the Python library for interacting with Spark. In the first lesson, you will learn about big data and how Spark fits into the big data ecosystem. In lesson two, you will be practicing processing and cleaning datasets to get comfortable with Spark’s SQL and dataframe APIs. In the third lesson, you will debug and optimize your Spark code when running on a cluster. In lesson four, you will use Spark’s Machine Learning Library to train machine learning models at scale.

What you will learn

  1. The Power of Spark
    • Understand the big data ecosystem
    • Understand when to use Spark and when not to use it
  2. Data Wrangling with Spark
    • Manipulate data with SparkSQL and Spark Dataframes
    • Use Spark for wrangling massive datasets
  3. Debugging and Optimization
    • Troubleshoot common errors and optimize their code using the Spark WebUI
  4. Machine Learning with Spark
    • Use Spark’s Machine Learning Library to train machine learning models at scale

Prerequisites and requirements

This course is ideal for students with programming and data analysis experience.

See the Technology Requirements for using Udacity.

Why take this course?

Spark is a top open source project used by the largest companies and startups around the world to efficiently analyze messy data sets.

Learn with the best.

  • David Drummond
    David Drummond

    VP of Engineering at Insight

  • Judit Lantos
    Judit Lantos

    Senior Data Engineer at Netflix