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.
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You will learn how to create data processing pipelines using PySpark
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You will learn machine learning with geospatial data using the Spark MLlib library
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You will learn data analysis using PySpark, MongoDB and Bokeh, inside of jupyter notebook
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You will learn how to manipulate, clean and transform data using PySpark dataframes
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You will learn basic Geo mapping
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You will learn how to create dashboards
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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?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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