Building Big Data Pipelines with PySpark + MongoDB + Bokeh

About Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Welcome to the

​Building Big Data Pipelines with PySpark & MongoDB & Bokeh​

course. In this course we will be building an intelligent data pipeline using big data technologies like

Apache Spark

and

MongoDB

. We will be building an

ETLP

pipeline,

ETLP

stands for

Extract Transform Load

and

Predict

. These are the different stages of the data pipeline that our data has to go through in order for it to become useful at the end. Once the data has gone through this pipeline we will be able to use it for building reports and dashboards for data analysis. The data pipeline that we will build will comprise of data processing using

PySpark

, Predictive modelling using Spark’s

MLlib

machine learning library, and data analysis using

MongoDB

and

Bokeh

.

You will learn how to create data processing pipelines using PySpark

You will learn machine learning with geospatial data using the Spark MLlib library

You will learn data analysis using PySpark, MongoDB and Bokeh, inside of jupyter notebook

You will learn how to manipulate, clean and transform data using PySpark dataframes

You will learn basic Geo mapping

You will learn how to create dashboards

You will also learn how to create a lightweight server to serve Bokeh dashboards