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Free Course
Master how to work with big data and build machine learning models at scale using Spark!
Estimated time
Approx. 10 Hours
Skill level
Intermediate
Prerequisites
See prerequisites in detail
In collaboration with
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
The Power of Spark
- Understand the big data ecosystem
- Understand when to use Spark and when not to use it
Data Wrangling with Spark
- Manipulate data with SparkSQL and Spark Dataframes
- Use Spark for wrangling massive datasets
Debugging and Optimization
- Troubleshoot common errors and optimize their code using the Spark WebUI
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
VP of Engineering at Insight
Judit Lantos
Senior Data Engineer at Netflix