Data Analytics with Pyspark

Data Analytics with Pyspark

PySpark helps you perform data analysis. It helps you to build more scalable analyses and data pipelines. This course starts by introducing you to PySpark's potential for performing analysis of large datasets. You'll learn how to interact with Spark from Python and connect to Spark on windows as local machine.

By the end of this course, you will not only be able to perform efficient data analytics but will have also learned to use PySpark to easily analyze large datasets at-scale in your organization.

This course will greatly appeal to data science enthusiasts, data scientists, or anyone who is familiar with Machine Learning concepts and wants to scale out his/her work to work with big data.

If you find it difficult to analyze large datasets that keep growing, then this course is the perfect guide for you!

Note: A working knowledge of Python assumed.

What You Will Learn

• Gain a solid knowledge of PySpark with Data Analytics concepts via practical use cases

• Run, process, and analyze large chunks of datasets using PySpark

• Utilize Spark SQL to easily load big data into DataFrames

• How to use PySpark SQL Functions.

• How you can extract data from multiple sources

We will using Pycharm as an IDE to run pyspark and python.

Learn the basics of Pyspark

Url: View Details

What you will learn

• Spark and Big Data Overview
• PySpark SQL Functions & Aggregations
• How to extract data from multiple sources

Rating: 4.2

Level: All Levels

Duration: 2 hours

Instructor: Wajahatullah Khan