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50 Hours of Big Data, PySpark, AWS, Scala, and Scraping
50 Hours of Big Data, PySpark, AWS, Scala, and Scraping

50 Hours of Big Data, PySpark, AWS, Scala, and Scraping: Big Data with Scala and Spark, PySpark and AWS, Data Scraping and Data Mining with Python, Mastering MongoDB for Beginners

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Can$63.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Mar 2022 54hrs 32mins 1st Edition
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Can$63.99
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Can$63.99
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Video Mar 2022 54hrs 32mins 1st Edition
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Can$63.99
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Can$63.99
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Key benefits

  • Data scraping and data mining for beginners to pro with Python
  • Clear unfolding of concepts with examples in Python, Scrapy, Scala, PySpark, and MongoDB
  • Master Big Data with PySpark and AWS

Description

Part 1 is designed to reflect the most in-demand Scala skills. It provides an in-depth understanding of core Scala concepts. We will wrap up with a discussion on Map Reduce and ETL pipelines using Spark from AWS S3 to AWS RDS (includes six mini-projects and one Scala Spark project). Part 2 covers PySpark to perform data analysis. You will explore Spark RDDs, Dataframes, a bit of Spark SQL queries, transformations, and actions that can be performed on the data using Spark RDDs and dataframes, the ecosystem of Spark and Hadoop, and their underlying architecture. You will also learn how we can leverage AWS storage, databases, computations, and how Spark can communicate with different AWS services. Part 3 is all about data scraping and data mining. You will cover important concepts such as Internet Browser execution and communication with the server, synchronous and asynchronous, parsing data in response from the server, tools for data scraping, Python requests module, and more. In Part 4, you will be using MongoDB to develop an understanding of the NoSQL databases. You will explore the basic operations and explore the MongoDB query, project and update operators. We will wind up this section with two projects: Developing a CRUD-based application using Django and MongoDB and implementing an ETL pipeline using PySpark to dump the data in MongoDB. By the end of this course, you will be able to relate the concepts and practical aspects of learned technologies with real-world problems. All the resources of this course are available at https://github.com/PacktPublishing/50-Hours-of-Big-Data-PySpark-AWS-Scala-and-Scraping

Who is this book for?

This course is designed for absolute beginners who want to create intelligent solutions, study with actual data, and enjoy learning theory and then putting it into practice. Data scientists, machine learning experts, and drop shippers will all benefit from this training. A basic understanding of programming, HTML tags, Python, SQL, and Node JS is required. However, no prior knowledge of data scraping, and Scala is needed.

What you will learn

  • Build ETL pipeline from AWS S3 to AWS RDS using Spark
  • Explore Spark/Hadoop applications, ecosystem, and architecture
  • Learn collaborative filtering in PySpark
  • Recognize the distinction between synchronous and asynchronous requests
  • Understand MongoDB CRUD, query operators, projection operators, and update operators
  • Build APIs for CRUD operations in MongoDB through Django

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 30, 2022
Length: 54hrs 32mins
Edition : 1st
Language : English
ISBN-13 : 9781803237039
Category :
Languages :
Concepts :
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Product Details

Publication date : Mar 30, 2022
Length: 54hrs 32mins
Edition : 1st
Language : English
ISBN-13 : 9781803237039
Category :
Languages :
Concepts :
Tools :

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Table of Contents

35 Chapters
Part 1 - Data Scraping and Data Mining for Beginners to Pro with Python Chevron down icon Chevron up icon
Requests Chevron down icon Chevron up icon
Beautiful Soup 4 (BS4) Chevron down icon Chevron up icon
CSS Selectors Chevron down icon Chevron up icon
Scrapy Chevron down icon Chevron up icon
Scrapy Project Chevron down icon Chevron up icon
Selenium Chevron down icon Chevron up icon
Project Selenium Chevron down icon Chevron up icon
Part 2 - Scala and Spark - Master Big Data with Scala and Spark Chevron down icon Chevron up icon
Scala Overview Chevron down icon Chevron up icon
Flow Control Chevron down icon Chevron up icon
Functions Chevron down icon Chevron up icon
Classes Chevron down icon Chevron up icon
Data Structures Chevron down icon Chevron up icon
Project for Scala and Spark Chevron down icon Chevron up icon
Part 3 - PySpark and AWS - Master Big Data with PySpark and AWS Chevron down icon Chevron up icon
Introduction to Hadoop, Spark Ecosystems and Architectures Chevron down icon Chevron up icon
Spark RDDs Chevron down icon Chevron up icon
Spark DFs Chevron down icon Chevron up icon
Collaborative Filtering Chevron down icon Chevron up icon
Spark Streaming Chevron down icon Chevron up icon
ETL Pipeline Chevron down icon Chevron up icon
Project - Change Data Capture / Replication On Going Chevron down icon Chevron up icon
Part 4 - MongoDB-Mastering MongoDB for Beginners (Theory and Projects) Chevron down icon Chevron up icon
Overview Chevron down icon Chevron up icon
Basic Mongo Operations Chevron down icon Chevron up icon
Basic Update Operation Chevron down icon Chevron up icon
Basic Read Operation Chevron down icon Chevron up icon
Basic Delete Operation Chevron down icon Chevron up icon
Query and projection operators Chevron down icon Chevron up icon
Update Operators Chevron down icon Chevron up icon
Mongo with Node Chevron down icon Chevron up icon
Mongo with Python Chevron down icon Chevron up icon
Django with Mongo Chevron down icon Chevron up icon
Spark with Mongo Chevron down icon Chevron up icon

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Tadeo Jan 09, 2024
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it is a complete and good course !!!
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