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Building Big Data Pipelines with PySpark + MongoDB + Bokeh

person icon Edwin Bomela

4.1

Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Build intelligent data pipelines with big data processing and machine learning technologies

updated on icon Updated on May, 2024

language icon Language - English

person icon Edwin Bomela

English [CC]

category icon Big Data,Business Intelligence

Lectures -25

Resources -1

Duration -5 hours

4.1

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Course Description

Welcome to the Building Big Data Pipelines with PySpark & MongoDB & Bokeh course. Inthis 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

Who this course is for:

  • Python Developers at any level
  • Developers at any level
  • Machine Learning engineers at any level
  • Data Scientists at any level
  • The curious mind
  • GIS Developers at any level

Goals

What will you learn in this course:

  • PySpark Programming

  • Data Analysis

  • Python and Bokeh

  • Data Transformation and Manipulation

  • Data Visualization

  • Big Data Machine Learning

  • Geo Mapping

  • Geospatial Machine Learning

  • Creating Dashboards

Prerequisites

What are the prerequisites for this course?

  • Basic Understanding of Python

  • Little or no understanding of GIS

  • Basic understanding of Programming concepts

  • Basic understanding of Data

  • Basic understanding of what Machine Learning is

Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
1 Lectures
  • play icon Introduction 09:30 09:30
Setup and Installations
6 Lectures
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Data Processing with PySpark and MongoDB
4 Lectures
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Machine Learning with PySpark and MLlib
3 Lectures
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Data Visualization
6 Lectures
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Creating the Data Pipeline Scripts
4 Lectures
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Source Code and Notebook
1 Lectures
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Instructor Details

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Edwin Bomela


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