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This plan includes
- Limited free courses access
- Play & Pause Course Videos
- Video Recorded Lectures
- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
- Lifetime Course Certificate
- Email & Chat Support
This plan includes
- Access to 11,000+ Courses
- Ads free experience Courses
- Play & Pause Course Videos
HD Video Recorded Lectures- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
- Lifetime Course Certificate
- Instructor Direct Support
- Email & Chat Support
- Cancel Anytime
What you'll 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
Course Overview
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
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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
Pre-requisites
- 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
Target Audience
- 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
Curriculum 25 Lectures 02:03:01
-
Section 1 : Introduction
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Section 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
-
Section 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
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Section 4 : Machine Learning with PySpark and MongoDB
- Lecture 1 :
- Data Pre-processing
- Lecture 2 :
- Building the Predictive Model
- Lecture 3 :
- Creating the Prediction Dataset
-
Section 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
-
Section 6 : Building 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
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Section 7 : Source Code and Notebook
- Lecture 1 :
- Source Code and Notebook
Our learners work at
Frequently Asked Questions
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Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic. -
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