Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Building Big Data Pipelines with PySpark + MongoDB + Bokeh, available at $49.99, has an average rating of 4, with 25 lectures, based on 68 reviews, and has 2408 subscribers.

You will learn about PySpark Programming Data Analysis Python and Bokeh Data Transformation and Manipulation Data Visualization Big Data Machine Learning Geo Mapping Geospatial Machine Learning Creating Dashboards This course is ideal for individuals who are Python Developers at any level or Developers at any level or Machine Learning engineers at any level or Data Scientists at any level or The curious mind or GIS Developers at any level It is particularly useful for Python Developers at any level or Developers at any level or Machine Learning engineers at any level or Data Scientists at any level or The curious mind or GIS Developers at any level.

Enroll now: Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Summary

Title: Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Price: $49.99

Average Rating: 4

Number of Lectures: 25

Number of Published Lectures: 25

Number of Curriculum Items: 25

Number of Published Curriculum Objects: 25

Original Price: R849.99

Quality Status: approved

Status: Live

What You Will Learn

PySpark Programming

Data Analysis

Python and Bokeh

Data Transformation and Manipulation

Data Visualization

Big Data Machine Learning

Geo Mapping

Geospatial Machine Learning

Creating Dashboards

Who Should Attend

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

Target Audiences

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

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 ETLPpipeline, ETLPstands for Extract Transform Loadand 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 MLlibmachine learning library, and data analysis using MongoDBand

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

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Setup and Installations

Lecture 1: Python Installation

Lecture 2: Installing Third Party Libraries

Lecture 3: Installing Apache Spark

Lecture 4: Installing Java (Optional)

Lecture 5: Testing Apache Spark Installation

Lecture 6: Installing MongoDB

Lecture 7: Installing NoSQL Booster for MongoDB

Chapter 3: Data Processing with PySpark and MongoDB

Lecture 1: Integrating PySpark with Jupyter Notebook

Lecture 2: Data Extraction

Lecture 3: Data Transformation

Lecture 4: Loading Data into MongoDB

Chapter 4: Machine Learning with PySpark and MLlib

Lecture 1: Data Pre-processing

Lecture 2: Building the Predictive Model

Lecture 3: Creating the Prediction Dataset

Chapter 5: Data Visualization

Lecture 1: Loading the Data Sources from MongoDB

Lecture 2: Creating a Map Plot

Lecture 3: Creating a Bar Chart

Lecture 4: Creating a Magnitude Plot

Lecture 5: Creating a Grid Plot

Chapter 6: Creating the Data Pipeline Scripts

Lecture 1: Installing Visual Studio Code

Lecture 2: Creating the PySpark ETL Script

Lecture 3: Creating the Machine Learning Script

Lecture 4: Creating the Dashboard Server

Chapter 7: Source Code and Notebook

Lecture 1: Source Code and Notebook

Instructors

EBISYS R&D
Big Data Engineering

Rating Distribution

1 stars: 0 votes

2 stars: 2 votes

3 stars: 8 votes

4 stars: 29 votes

5 stars: 29 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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