What You Will Learn!
- Spark and Big Data Overview
- PySpark SQL Functions & Aggregations
- How to extract data from multiple sources
- Resilient Distributed Dataset (RDD)
- Matplotlib with PySpark for Visualizations
Description
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.
Who Should Attend!
- Python developers who are curious about learning pyspark data analytics
