Python Web Scraping and Web Development Technologies
Data Finding Techniques to scrap data from the web
Implementing Web Scraping in Python with BeautifulSoup
Build a Python web scraper using Selectolax
How to perform Python Web Scraping using Selenium
How To Use Playwright For Web Scraping with Python
General Best Practices To Follow When Conducting Web Scraping
Advanced Web Scraping Topics
Web scraping involves the retrieval and parsing of unstructured data from the Web, and the Python community has developed a variety of powerful tools for this purpose.
In this complete course you wil learn how to scrap and parse informations from the internet using the Python libraries and frameworks such as: Beautiful Soup, Requests, Selenium, Selectolax & Playwright.
Therefore, I recommend that you acquire this skill with me by taking this course that will guide you from being a beginner to an expert in web scraping using Python as programming language.
The installation and preparation of the technical environment is well explained and Practical works are included for each concept to emphasize and illustrate the concepts presented in the course.
The different sections of this course are as follows:
– Python Installation
– Python Web Scraping and Web Development Technologies
– Data Finding Techniques to scrap data from the web
– Implementing Web Scraping in Python with BeautifulSoup
– Build a Python web scraper using Selectolax
– How to perform Python Web Scraping using Selenium
– How To Use Playwright For Web Scraping with Python
– General Best Practices To Follow When Conducting Web Scraping
– Advanced Web Scraping Topics
All this will be covered step by step, so that you can leverage the skills you learn in this course to build even bigger and better web scrapers.
Understand the fundamentals of Web Scraping
Web Scraping with Python Beautiful Soup and Requests
Exporting data extracted by Beautifulsoup into CSV, Excel files
When the webpage structure is so complicated, making it difficult to extract specific pieces of data, or when you need to open so many pages to extract data from each of them, the manual process can become boring and time-wasting, and that is when automated Web Scraping can make the process more efficient and effective.
Web scraping is the practice of gathering data from internet automatically by computer program without using API and web browser.
Instead of copy pasting important data by a human from a web browser visiting a website, web scraping can automate the process. Web scraping is now very important for a data scientist. A data scientist analysis data collected from various media. Now most of the data comes from different websites. As Python programming is very popular for harvesting data, many data scientist use Python programming to solve that.
I created this course as short and useful as possible. Within short period of time, you can learn all the important topics and techniques about web scraping using Python. So using the same technique you can apply to scrap other similar webpage as well using Python.
This Web Scraping course covers the following topics:
So let’s start your Web Scraping real-life project.
Understand the basics of web scraping
Understand how to setup a manual data pipeline
Learn how to modularize code into functions
See how to setup a basic dashboard in Flask
This video series will walk through building a simple blogging analytics dashboard in Python.
Here is a synopsis of each video:
Everything in the project is done manually to show the steps between. I plan to upload a 2nd version that shows how to automate the entire pipeline.
Web Scraping Essential Skills in less than one hour!!!
Practical Web Scraping Tips and Tricks
If you want to be a creative data scientist, web scraping is an indispensible capability you should learn. In this effort, you should start from understanding and establishing essential skills and tools of web scraping.
Learn them.
Practice a lot with them through solving real-life problems.
This is the way to proceed in a more natural evolution and much more intuitively so that you are able to ask the right questions and come up with solutions.
“Web Scraping with Python 101: Build Scrapy Essential Skills” is the course aimed at these fundamentals through Scrapy, Python’s popular web scraping framework.
This is the starter course of a series to master web-scraping and Scrapy from basic skills to advanced concepts, from deep insights on the tools to the most practical real-life data science example utilizing web scraping on this platform, a depth and perspective unique to this course series that collectively have gathered more than 10000 students in months.
Two remaining questions:
First, who is this course aiming?
This course is for beginners. Not for beginners to programming, but beginners to Web Scraping. Persons who have seen it, thought about learning it, have limited time. Its about showing them how to start, and proceed and that web scraping is not earth science.
Second, what exactly is in this course?
In this course;
We will start with what is web scraping and why it is important.
We fill define the 3 pillars of webscraping: crawling, scraping and keeping the connection.
We will run our pillars on a living ‘amazon’ example.
We will finish with practical recommendations on each pillar and on a guide to how to proceed.
A fully refined course to perfectly fit your busy schedule.
Last but not the least; be sure to watch the course video on this very landing page.
See you in the lectures!
Very Respectfully,
Tarkan Aguner
Automate the process of gathering unstructured data which is in the form of raw HTML.
Learn to web scrap Financial News of specific listed companies on the Stock Market.
Use BeautifulSoup4 Python library for web scraping – Install, Exception Handling, Advanced HTML Parsing.
How to traverse a single domain to fetch data from many HTML pages.
Process gathered (scrapped) data and transform it into structured format JSON and save as CSV.
Why this course?
We often have plenty of unstructured data available for free on the internet. Some of this data may be useful for combining with other structured or unstructured data available in the organization. What if I could fetch the desired unstructured data from web, transform it into structured format, and combine it with my other data, preprocess combined data, so that I can extract valuable insights to facilitate quick and better data-driven decision making?
Good news is that there are some techniques such as Web Scraping which can help us solve the problem of data gathering at scale and build curated datasets. In this course we will help you achieve this goal. Following are our Learning Objectives for this course.
In this course we are giving you hands-on experience of how to build and automate process of generating curated dataset from raw HTML text, scraped from web.
