Spark and Python for Big Data with PySpark free download

What you’ll learn in Spark and Python for Big Data with PySpark

To analyze Big Data, combine Python and Spark.
Learn about the new DataFrame Syntax in Spark 2.0.
Work on consulting projects that are modeled after real-life scenarios!
Use Logisitic Regression to categorize customer churn.
For classification, use Spark and Random Forests.
Gradient Boosted Trees are a feature of Spark that you should learn how to use.
Make powerful machine learning models with Spark’s MLlib library.
Get acquainted with the DataBricks Platform!
For Big Data Analysis, get started with Amazon Web Services EC2.
Discover how to use the AWS Elastic MapReduce Service.
Learn how to use a Spark Environment to take advantage of Linux’s power!
With Spark and Natural Language Processing, you can make a spam filter!
Analyze Tweets in Real Time with Spark Streaming!

Specification

• Skills in any programming language (preferably Python) are required.
• A strong internet connection (or 20 GB of free space on your local computer) is required for AWS.

Description

Learn about Spark, the most recent Big Data technology, and how to use it with Python, one of the most popular programming languages.
The ability to analyze large data sets is one of the most valuable technology skills, and this course is specifically designed to get you up to speed on Apache Spark, one of the best technologies for this task! Top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and others all use Spark to solve their big data problems!

This course will start with a crash course in Python and progress to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! After that, we’ll go over how to use the MLlib Machine Library with the DataFrame syntax and Spark, with exercises and Mock Consulting Projects along the way to put you in a real-world situation where you’ll need to apply your new skills to solve a real problem!