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50 Hrs Big Data Mastery: PySpark, AWS, Scala & Data Scraping

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50 Hrs Big Data Mastery: PySpark, AWS, Scala & Data Scraping, available at $79.99, has an average rating of 3.8, with 624 lectures, 31 quizzes, based on 207 reviews, and has 2038 subscribers.

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You will learn about Introduction and importance of this course in this day and age Approach all essential concepts from the beginning Clear unfolding of concepts with examples in Python,Scrapy, Scala, PySpark and MongoDB All theoretical explanations followed by practical implementations Data Scraping & Data Mining for Beginners to Pro with Python Master Big Data with Scala and Spark Master Big Data With PySpark and AWS Mastering MongoDB for Beginners Building your own AI applications This course is ideal for individuals who are People who are absolute beginners. or People who want to make smart solutions. or People who want to learn with real data. or People who love to learn theory and then implement it practically. or Data Scientists, Machine learning experts and Drop Shippers. It is particularly useful for People who are absolute beginners. or People who want to make smart solutions. or People who want to learn with real data. or People who love to learn theory and then implement it practically. or Data Scientists, Machine learning experts and Drop Shippers.

Enroll now: 50 Hrs Big Data Mastery: PySpark, AWS, Scala & Data Scraping

Summary

Title: 50 Hrs Big Data Mastery: PySpark, AWS, Scala & Data Scraping

Price: $79.99

Average Rating: 3.8

Number of Lectures: 624

Number of Quizzes: 31

Number of Published Lectures: 623

Number of Published Quizzes: 31

Number of Curriculum Items: 655

Number of Published Curriculum Objects: 654

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Introduction and importance of this course in this day and age
  • Approach all essential concepts from the beginning
  • Clear unfolding of concepts with examples in Python,Scrapy, Scala, PySpark and MongoDB
  • All theoretical explanations followed by practical implementations
  • Data Scraping & Data Mining for Beginners to Pro with Python
  • Master Big Data with Scala and Spark
  • Master Big Data With PySpark and AWS
  • Mastering MongoDB for Beginners
  • Building your own AI applications

Who Should Attend

  • People who are absolute beginners.
  • People who want to make smart solutions.
  • People who want to learn with real data.
  • People who love to learn theory and then implement it practically.
  • Data Scientists, Machine learning experts and Drop Shippers.

Target Audiences

  • People who are absolute beginners.
  • People who want to make smart solutions.
  • People who want to learn with real data.
  • People who love to learn theory and then implement it practically.
  • Data Scientists, Machine learning experts and Drop Shippers.

Welcome to the comprehensive Big Data and Data Science bundle, where you’ll embark on an educational journey covering a wide range of essential skills and technologies. This course equips you with expertise in Scala, PySpark, AWS, Data Scraping, Data Mining, and MongoDB. Whether you’re an absolute beginner or possess some programming knowledge, this course provides in-depth coverage of these critical topics.

I. Scala:

Scala may not be the most popular coding language, but it’s undeniably one of the most sought-after skills for data scientists and data engineers. This course is meticulously designed to make Scala simple to grasp and implement. You’ll engage with quizzes and mini-projects to reinforce your learning, making your Scala experience seamless. 

Key Highlights:

  • High Demand Skill: Scala is in high demand in the industry, and this course ensures you acquire essential skills

  • Practical Learning: Quizzes and mini-projects serve as building blocks for a comprehensive understanding of Scala

  • Hands-on Experience: Gain practical experience by working on a Scala Spark project

  • Versatility: Scala is a powerful language suitable for a wide range of applications, from web development to machine learning

Learning Materials:

  • Comprehensive Scala tutorials

  • Scala quizzes and assessments

  • Hands-on Scala Spark project

  • Scala code examples and exercises

II. PySpark and AWS:

Python and Apache Spark are at the forefront of Big Data analytics, and PySpark bridges the gap between them. In this section, you’ll start with the basics and progress to advanced data analysis. You’ll work with PySpark for data analysis, explore Spark RDDs, Dataframes, and Spark SQL queries, and delve into Spark and Hadoop ecosystems. Additionally, you’ll discover how to leverage AWS cloud services with Spark. 

Key Highlights:

  • Python and Spark Integration: Master the art of using Python and Spark together for effective Big Data analysis

  • Comprehensive Coverage: Explore Spark RDDs, Dataframes, Spark SQL queries, and seamlessly integrate with AWS

  • Hands-on Practice: Apply your knowledge through practical exercises and projects

Learning Materials:

  • In-depth PySpark and AWS tutorials

  • PySpark quizzes and assessments

  • AWS integration guides and examples

  • PySpark code samples and hands-on projects

III. Data Scraping and Data Mining:

Data scraping involves extracting data from websites and APIs, making it a valuable skill for data professionals. This section is tailored for beginners, starting with foundational concepts and gradually delving into advanced techniques through practical implementations. Hands-on projects are a pivotal part of this segment, allowing you to learn through experimentation and real-world applications. 

Key Highlights:

  • Beginner-Friendly: Perfect for individuals new to data scraping and mining

  • Practical Implementation: Gain deep insights through hands-on projects and real-world examples

  • Lucrative Career: Data scraping offers rewarding career prospects and competitive salaries

Learning Materials:

  • Comprehensive Data Scraping and Mining tutorials

  • Hands-on data extraction projects

  • Data scraping and mining quizzes and assessments

  • Data scraping code samples and automation scripts

IV. MongoDB:

This section introduces you to MongoDB, a popular NoSQL database. You’ll learn the fundamentals of MongoDB, including Create, Read, Update, and Delete operations. Dive deep into MongoDB query and project operators, enhancing your understanding of NoSQL databases. Two comprehensive projects will provide you with practical experience using MongoDB in Django and implementing an ETL (Extract, Transform, Load) pipeline with PySpark. 

Key Highlights:

  • NoSQL Proficiency: Develop expertise in MongoDB, a highly sought-after NoSQL database

  • Hands-on Projects: Apply your knowledge to real-world scenarios and gain practical skills

  • Versatile Skills: MongoDB is invaluable for data management and analytics

Learning Materials:

  • MongoDB fundamentals and advanced tutorials

  • Hands-on MongoDB projects, including Django integration and ETL pipeline development

  • MongoDB quizzes and assessments

  • MongoDB code examples and best practices

Course Benefits:

Upon completing this comprehensive course successfully, you will be proficient in implementing projects from scratch that require expertise in Data Scraping, Data Mining, Scala, PySpark, AWS, and MongoDB. You’ll be adept at connecting theoretical concepts to real-world problem-solving, efficiently extracting data from websites, and be well-prepared for various data-related roles. 

Learning Materials:

  • Video lectures and tutorials.

  • Quizzes, assessments, and solutions.

  • Hands-on projects with step-by-step guidance.

  • Code examples and templates.

  • Reference materials and best practices. 

Enroll now to embark on your journey toward mastering Big Data and Data Science comprehensively!

Who Should Enroll:

  • Ideal for beginners or those looking to apply theoretical knowledge in practical scenarios

  • Aspiring data scientists and machine learning experts

  • Individuals aiming to excel in the realm of Big Data and Data Science

What You’ll Learn:

  • Proficiency in implementing projects requiring expertise in Data Scraping, Data Mining, Scala, PySpark, AWS, and MongoDB

  • Efficient data extraction from websites

  • Skills applicable to various data-related roles

Why This Course:

  • High demand for Scala skills in the industry

  • Comprehensive coverage of PySpark, AWS, Data Scraping, Data Mining, and MongoDB

  • Hands-on experience through projects and practical exercises

  • Versatile skills for a wide range of applications

List of Keywords:

  • Big Data

  • Data Science

  • Scala

  • PySpark

  • AWS

  • Data Scraping

  • Data Mining

  • MongoDB

  • NoSQL Database

  • Data Extraction

  • Data Analysis

Course Curriculum

Chapter 1: Data Scraping & Data Mining for Beginners to Pro with Python

Lecture 1: Introduction: Why Data Scraping

Lecture 2: Introduction: Applications of Data Scraping

Lecture 3: Introduction: Introduction of Instructor

Lecture 4: Introduction: Introduction to Course, Scraping, Tools

Lecture 5: Introduction: Projects Overview

Lecture 6: Introduction: Request for Your Honest Review

Lecture 7: Requests: Introduction to Python Requests

Lecture 8: Requests: Hand on with Requests

Lecture 9: Requests: Extracting Quotes Manually

Lecture 10: Requests: Quiz(Extracting Authors)

Lecture 11: Requests: Solution(Extracting Authors)

Lecture 12: Requests: Pagination

Lecture 13: Requests: Quiz(Extracting Author and Quotes)

Lecture 14: Requests: Solution 01(Extracting Author and Quotes)

Lecture 15: Requests: Solution 02(Extracting Author and Quotes)

Lecture 16: Requests: Ajax Requests

Lecture 17: Requests: Ajax Requests for Cricinfo

Lecture 18: Requests: Ajax Requests Paggination

Lecture 19: Requests: Quiz(Extracting Top Stats from Cricinfo)

Lecture 20: Requests: Solution 01(Extracting Top Stats from Cricinfo)

Lecture 21: Requests: Solution 02(Extracting Top Stats from Cricinfo)

Lecture 22: Beautiful Soap 4(BS4): Introduction to BS4

Lecture 23: Beautiful Soap 4(BS4): Quiz(Difference between Requests and BS4)

Lecture 24: Beautiful Soap 4(BS4): Solution(Difference between Requests and BS4)

Lecture 25: Beautiful Soap 4(BS4): Hands on with BS4

Lecture 26: Beautiful Soap 4(BS4): Extracting Data from Tree

Lecture 27: Beautiful Soap 4(BS4): Extracting Quotes from the Website

Lecture 28: Beautiful Soap 4(BS4): Quiz(Extracting Author Names)

Lecture 29: Beautiful Soap 4(BS4): Solution(Extracting Author Names)

Lecture 30: Beautiful Soap 4(BS4): Attributes of Tags in BS4

Lecture 31: Beautiful Soap 4(BS4): Multi Valued Attributes of Tags in BS4

Lecture 32: Beautiful Soap 4(BS4): Scraping Movie Names from IMDB

Lecture 33: Beautiful Soap 4(BS4): Quiz(Getting the Rattings,Year,Name of the Movie)

Lecture 34: Beautiful Soap 4(BS4): Solution 01(Getting the Rattings,Year,Name of the Movie)

Lecture 35: Beautiful Soap 4(BS4): Solution 02(Getting the Rattings,Year,Name of the Movie)

Lecture 36: Beautiful Soap 4(BS4): Scraping Time,Genre and Releasing Date from IMDB 01

Lecture 37: Beautiful Soap 4(BS4): Scraping Time,Genre and Releasing Date from IMDB 02

Lecture 38: Beautiful Soap 4(BS4): Combining Two Requests Data for IMDB

Lecture 39: Beautiful Soap 4(BS4): Movies Recommender System (CreatingMovie Url)

Lecture 40: Beautiful Soap 4(BS4): Movies Recommender System (Creating Director Url)

Lecture 41: Beautiful Soap 4(BS4): Movies Recommender System using BS4(Getting Top 4 Movies)

Lecture 42: Beautiful Soap 4(BS4): Movies Recommender System using BS4(Merge All Requests Together)

Lecture 43: CSS Selectors: Introduction to CSS Selectors

Lecture 44: CSS Selectors: CSS Selectors Handson(Tags)

Lecture 45: CSS Selectors: Quiz(Tags)

Lecture 46: CSS Selectors: Solution(Tags)

Lecture 47: CSS Selectors: CSS Selectors Handson(Decendants, Id, Class)

Lecture 48: CSS Selectors: Quiz(Descendants)

Lecture 49: CSS Selectors: Solution(Descendants)

Lecture 50: CSS Selectors: Quiz(ID)

Lecture 51: CSS Selectors: Solution(ID)

Lecture 52: CSS Selectors: Solution(Class)

Lecture 53: CSS Selectors: Solution(Class)

Lecture 54: CSS Selectors: CSS Selectors Handson(Nested Tags, ID Tags, Class Tags)

Lecture 55: CSS Selectors: Quiz(Class with Tag)

Lecture 56: CSS Selectors: Solution(Class with Tag)

Lecture 57: CSS Selectors: CSS Selectors Handson(Coma Seprator, Universial Selectors

Lecture 58: CSS Selectors: Quiz(Combining Two Selectors)

Lecture 59: CSS Selectors: Solution(Combining Two Selectors)

Lecture 60: CSS Selectors: CSS Selectors Handson(Sibling Notations and Direct Child)

Lecture 61: CSS Selectors: Quiz(Adjacent Sibling)

Lecture 62: CSS Selectors: Solution(Adjacent Sibling)

Lecture 63: CSS Selectors: Quiz(General Sibling)

Lecture 64: CSS Selectors: Solution(General Sibling)

Lecture 65: CSS Selectors: CSS Selectors Handson(Child Selectors)

Lecture 66: CSS Selectors: Quiz(First Child)

Lecture 67: CSS Selectors: Solution(First Child)

Lecture 68: CSS Selectors: Quiz(Only Child)

Lecture 69: CSS Selectors: Solution(Only Child)

Lecture 70: CSS Selectors: Quiz(Last Child)

Lecture 71: CSS Selectors: Solution(Last Child)

Lecture 72: CSS Selectors: CSS Selectors Handson (Nigations, Attributes)

Lecture 73: CSS Selectors: Quiz(Negation)

Lecture 74: CSS Selectors: Solution(Negation)

Lecture 75: CSS Selectors: CSS Selectors Handson (Attributes, Attributes Values)

Lecture 76: CSS Selectors: Quiz(Attributes Values)

Lecture 77: CSS Selectors: Solution(Attributes Values)

Lecture 78: CSS Selectors: CSS Selectors Handson (Attributes Wild Cards Values)

Lecture 79: CSS Selectors: Quiz(Attributes Wild Card)

Lecture 80: CSS Selectors: Solution(Attributes Wild Card)

Lecture 81: Scrapy: Introduction to Scrapy

Lecture 82: Scrapy: Comparison of Scrapy and Requests

Lecture 83: Scrapy: Scrapy at a Glance Documentation

Lecture 84: Scrapy: Getting Started with Scrapy

Lecture 85: Scrapy: Running Documentation Spider 1

Lecture 86: Scrapy: Running Documentation Spider 2

Lecture 87: Scrapy: Writing Spider from the Scratch

Lecture 88: Scrapy: Understanding the Response(url, Status)

Lecture 89: Scrapy: Understanding the Response(headers)

Lecture 90: Scrapy: Understanding the Response(values in headers)

Lecture 91: Scrapy: Understanding the Response(body)

Lecture 92: Scrapy: Understanding the Response(request)

Lecture 93: Scrapy: Understanding the Response(meta)

Lecture 94: Scrapy: Understanding the Response(flags, certificate, ip_address, copy)

Lecture 95: Scrapy: Understanding the Response(replace, urljoin, follow, follow_all)

Lecture 96: Scrapy: Response CSS and Scrapy Shell

Lecture 97: Scrapy: Extracting quotes

Lecture 98: Scrapy: Understanding Nested selectors

Lecture 99: Scrapy: Extracting the Author and Quotes

Instructors

Rating Distribution

  • 1 stars: 3 votes
  • 2 stars: 5 votes
  • 3 stars: 20 votes
  • 4 stars: 62 votes
  • 5 stars: 117 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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