только у нас скачать шаблон dle скачивать рекомендуем

Фото видео монтаж » Видео уроки » Видео уроки web-design » Web Scraping: Extracting Price Data for Market Research

Web Scraping: Extracting Price Data for Market Research

Web Scraping: Extracting Price Data for Market Research

Web Scraping: Extracting Price Data for Market Research
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.05 GB | Duration: 2h 30m



Learn web scraping to extract price data from Amazon and Zillow using Python and Beautiful Soup

What you'll learn
Learn how to perform web scraping on Amazon and Zillow
Learn how to extract and collect data from several different websites
Learn how to convert data to CSV file and download it automatically
Learn how to monetise web scraping and potential business models related to web scraping
Learn how to automate web scraping using ChatGPT

Requirements
No previous experience in programming or web scraping is required
Willingness to learn and pay close attention to details

Description
Welcome to Web Scraping: Extracting Price Data for Market Research course. This is basically a project based course where you will extensively learn how to do web scraping, extracting and collecting various data from several different websites and save them in a structured format, organised and neat in spreadsheet or perhaps your own database. In addition, this course also comes with two projects where you will be fully guided step by step to perform web scraping, extracting and collecting data from websites efficiently. The first project is to perform web scraping on Amazon marketplace website to extract and collect all data related to price and other product specifications as the data source for conducting market research. Meanwhile, the second project is also similar to the first project, where you will be guided step by step on how to perform web scraping on real estate websites to extract and collect data related to price and other property specifications as the data source for conducting real estate market research. To perform the web scraping, we are going to use the Python programming language alongside several Python libraries for web scraping, for example Beautiful Soup, Scrapy, and Selenium. At the end of the course, you will also learn several different ways to monetise your expertise in web scraping as well as potential business models related to web scraping that you can start.First of all, before getting into the course and the projects, we need to ask ourselves this question, why should we learn web scraping? well , even though there are many reasons why you should learn this useful technique, the one that is the most important among other reasons is the fact that web scraping enables you to extract and collect data from multiple different websites or sources quickly and efficiently, web scraping even allows you to save all the data in a structured format. Hence, web scraping has always been considered as one of the most powerful tools to conduct market research for many different types of products, starting from daily goods, foods, or even real estate. Lastly, for those of you who might not be very confident with your Python programming skills, there is nothing you should be worried about since this course also comes with a basic Python training session where you will be prepared with all skills and knowledge that you need to master before getting into the actual project.Things you are going to learn in basic Python training session:Different data types in Python (string, integer, float, and boolean)Function and parameters in PythonRequests library in PythonBeautiful Soup library in PythonThings you are going to learn in the projects:Performing web scraping on Amazon websitePerforming web scraping on Zillow websiteConverting and downloading data as CSV fileData formatting with JSONAutomating web scraping with ChatGPTStrategies to monetise web scraping and potential business models related to web scraping

Overview
Section 1: Introduction

Lecture 1 Introduction to the Course

Lecture 2 Highlight of the Course

Lecture 3 Whom This Course is Intended for?

Section 2: Tools, IDE, and Libraries

Lecture 4 Tools, IDE, and Libraries

Section 3: Introduction to Web Scraping

Lecture 5 Introduction to Web Scraping

Lecture 6 How Web Scraping Works?

Lecture 7 General Overview of the Projects

Section 4: Setting Up All Required Tools

Lecture 8 Setting Up All Required Tools

Section 5: Basic Python Training Session

Lecture 9 Basic Python Training Session

Lecture 10 Data Types

Lecture 11 Function & Parameter

Lecture 12 Requests Library

Lecture 13 Beautiful Soup Library

Section 6: Project 1: Amazon Web Scraping

Lecture 14 Installing & Importing Libraries for Project 1

Lecture 15 Building Amazon Scraper Function

Lecture 16 Converting Amazon Data to CSV

Section 7: Project 2: Zillow Web Scraping

Lecture 17 Installing & Importing Libraries for Project 2

Lecture 18 Scrapeak API

Lecture 19 Building Property Listing Function

Lecture 20 Converting Zillow Data to CSV

Section 8: Testing Web Scraping Projects

Lecture 21 Testing Amazon Web Scraping Project

Lecture 22 Testing Zillow Web Scraping Project

Section 9: Automating Web Scraping with ChatGPT

Lecture 23 Automating Web Scraping with ChatGPT

Section 10: Strategies to Monetise Web Scraping

Lecture 24 Strategies to Monetise Web Scraping

Section 11: Conclusion & Summary

Lecture 25 Conclusion & Summary

Python learners or enthusiasts who have interest in learning web scraping,Entrepreneurs who have interest in conducting product or market research,Business or data analyst who want to learn gathering data from several different sources quickly and efficiently

HOMEPAGE


  https://www.udemy.com/course/web-scraping-extracting-price-data-for-market-research/ 


DOWNLOAD


https://rapidgator.net/file/88a96bad59e8bf5480ef4bbe4a5dce94/wea-for-market-research.rar.html
https://uploadgig.com/file/download/81577D7C144556af/wea-for-market-research.rar
Poproshajka



Информация
Посетители, находящиеся в группе Гости, не могут оставлять комментарии к данной публикации.