Description
Comprehensive Course Description:
Data scraping is the technique of extracting data from the internet. Data scraping is used for getting the data available on different websites and APIs. This also involves automating the web flows for extracting the data from different web pages.
The course ‘Data Scraping and Data Mining from Beginner to Professional’ is crafted to cover the topics that result in the development of the most in-demand skills in the workplace. These topics will help you understand the concepts and methodologies with regard to Python. The course is:
Easy to understand.
Imaginative and descriptive.
Comprehensive.
Practical with live coding.
Full of quizzes with solutions.
Rich with state-of-the-art and updated knowledge of this field.
This course is designed for beginners. We’ll spend sufficient time to lay a solid groundwork for newbies. Then, we will go far deep gradually with a lot of practical implementations where every step will be explained in detail.
As this course is essentially a compilation of all the basics, you will move ahead at a steady rate. You will experience more than what you have learned. At the end of every concept, we will be assigning you Home Work/assignments/activities/quizzes along with solutions. They will assess / (further build) your learning based on the previous data scraping and data mining concepts and methods. Most of these activities are designed to get you up and running with implementations.
The 4 hands-on projects included in this course are the most important part of this course. These projects allow you to experiment for yourself with trial and error. You will learn from your mistakes. Importantly, you will understand the potential gaps that may exist between theory and practice.
Data Scraping is undoubtedly a rewarding career that allows you to solve some of the most interesting real-world problems. You will be rewarded with a fabulous salary package, too. With a core understanding of Data Scraping, you can fine-tune your workplace skills and ensure emerging career growth.
So, without further delay, get started with this course and pursue the knowledge that can sharpen your skills.
Teaching is our passion:
We strive to create updated and workplace-relevant online tutorials that could help you in understanding the concepts adequately. Our aim is to create a strong basic understanding for our students before moving onward to the advanced version. We have added enough exercises into the course. You will be able to grasp the concepts easily, and you will be inspired to think for yourself in regard to the right solution and implement it. High-quality video content, descriptive course material, assessment questions, course notes, and handouts are some of the perks of this course. Please approach our friendly team in case of any queries, and we assure you we will respond as quickly as possible.
Course Content:
The comprehensive and engaging course consists of the following topics:
1. Introduction:
a. Intro
i. Why Data Scraping?
ii. Applications of Data Scraping
iii. Introduction of Instructor
iv. Introduction to Course, Scraping, Tools
v. Projects Overview
2. Requests Module:
a. Getting Started with Requests Module
i. Introduction to Python Requests and Installations
ii. Going Through the Documentation
b. Extracting Data
i. Sending a request to the server
ii. Getting a response from the server
iii. Parsing the data
iv. Controlling pagination
v. Understanding Ajax populated data
vi. Parsing Ajax response data
3. Beautiful Soup (BS4):
a. Getting Started with Beautiful Soup
i. Introduction to Beautiful Soup
ii. Going Through the Documentation
b. Hands-on with BS4 Parser
i. Extracting data using BS4 parser
ii. Developing an understanding of BS4 parser functions
iii. Attributes of tags
iv. Multi-valued attributes of tags
v. Merge data from two different requests.
c. Project
i. Building movie recommender system by getting live data from IMDB
4. CSS Selectors:
a. Getting Started with CSS Selectors
i. Introduction to CSS Selectors
b. Hands-on with the CSS Selectors
i. Descendants, Id, Class-based selection
ii. Nested Tags, ID Tags, Class Tags based selection
iii. Coma Separator, Universal Selectors based selection
iv. Sibling Notations, Direct Child based selection
v. Child Selectors based selection
vi. Negations, Attributes based selection
vii. Attributes, Attributes values-based selection
viii. Attributes Wild Cards values-based selection
5. Scrapy:
a. Getting Started with Scrapy
i. Introduction to Scrapy
ii. Going through the documentation
b. Hands-on with Scrapy
i. Developing the understanding of Spider flow.
ii. Creating our Scrapy project and understanding the framework
iii. Writing Spiders from scratch.
iv. Understanding the Response object along with all its param including url, status, headers, body, request, meta, flags, certificate, ip_address, copy, replace, urljoin, follow, follow_all.
v. Working on Scrapy shell.
vi. Understanding request flow in Scrapy.
vii. Applying CSS selectors to Scrapy response for getting data.
viii. Extracting nested data from the website.
ix. Combine Data from multiple callbacks.
c. Projects
i. Scraping IMDB
ii. Getting products information from HUGO BOSS
6. Selenium:
a. Getting started with Selenium
i. Introduction to Selenium
b. Hands-on with Scrapy
i. Configuring the web driver.
ii. Parse response and extract the required data
iii. Automating website flow
iv. Navigating the website with form filling
c. Project
i. Language translation system using deepL website
After completing this information-packed course successfully, you will be able to:
Implement any project from scratch that requires Data Scraping knowledge.
Relate the concepts and practical aspects of Data Scraping with real-world problems.
Know the theory and practical aspects of Data Scraping concepts.
Gather data from websites in the smartest way.
Who this course is for:
People who are quite beginners and know absolutely nothing about Data Scraping.
People who want to make smart solutions.
People who want to learn Data Scraping with real data.
People who love to learn theory and then implement it using Python.
Who this course is for:
People who are quite beginners and know absolutely nothing about Data Scraping.
People who want to make smart solutions.
People who want to learn Data Scraping with real data.
People who love to learn theory and then implement it using Python.
People who want to learn Data Scraping along with its implementation in realistic projects.
Data Scientists.
Machine learning experts.
Drop Shippers.
Requirements
Basic understanding of HTML tags.
Familiarity with Python.
No prior knowledge of data scraping is needed. You start right from the basics and then gradually build your knowledge of the subject.
A willingness to learn and practice.
Since we teach by practical implementations, practice is a must thing to do.
Last Updated 3/2021
