Welcome to the wonderful online course on Apache Spark.

Apache Spark is an open source general purpose cluster computing system that has capabilities for iterative computation that can process large pieces of data without requiring human intervention. Though its primary function is as a distributed computing engine, it also includes libraries dedicated to machine learning and graph processing tasks for applications such as artificial intelligence.

PySpark is a Python-based implementation of Apache Spark, which distributes computations in memory, on CPUs, or on clusters of machines using in-memory data caching. This lets you run large-scale analytics jobs interactively. Python is a scripting language that’s easy to learn and fun to use! With Spark, you can now bring the power of machine learning directly into your code without having to copy and paste blocks of code from notebooks.

In this course, you will cover:-

• Getting started with Apache Spark introduction.

• Get an Overview of Spark.

• Learn how to Install Spark and setup using VirtualBox.

• Learn how to Install and setup using AWS EC2.

• Learn about the Data Frame and its implementation in Spark.

• Also learn about Machine Learning in Spark.

• Learn about Linear Regression and its implementation using MLlib.

• Learn about Logistic Regression and its implementation using MLlib.

• Learn about SVM Classifier and its implementation using MLlib.

• Learn about K nearest Neighbor and its implementation using MLlib.

• Learn about Naive Bayes and its implementation using MLlib.

• Learn about Tree Based Algorithms and its implementation.

After finishing this course, you will become an expert on Apache Spark. We are also providing quizzes.

You will also have access to all the resources used in this course.

Instructor Support - Quick Instructor Support for any queries.

Enroll now and make the best use of this course.