Web Scraping and API Fundamentals in Python
Sign up to
preview the program
Create a free account and start learning data science today.create free account
Our graduates work at exciting places:
In this first section, we will discuss what the course covers, why you need to learn Web Scraping and give you some notes on the ethics of scraping.
Setting Up the Environment
In this part of the course, we will explain to you how to set up Python 3 and then load up Jupyter. We’ll also show you what the Anaconda Prompt is and how we use it to download and import new modules.
Working with APIs
Here we will introduce what APIs are and how to use them. In order to do that, we will discuss the popular data exchange format JSON, as well as HTTP requests and the Python library to submit them – ‘requests’. At the end of the section, we will show you how to deal with an API that requires registration.
Web Scraping relies on extracting information from the source code of webpages. Thus, a general understanding of HTML is required. This section is a short crash course for those that are not familiar with HTML. It is meant as an intuitive look into the basics, not a comprehensive guide.
Web Scraping with Beautiful Soup
After familiarizing with HTML, we are ready to delve into the Web Scraping itself. We will now introduce the “Beautiful Soup” package and explore its capabilities.
Practical Project: Scraping Rotten Tomatoes
Now that we’ve seen what Beautiful Soup can do, we will devote this section to practicing our newly formed skills. We are going to obtain information about movies from a ‘Rotten Tomatoes’ rank list.
Scraping HTML Tables
In this short section, we will discuss an easy way to scrape HTML tables.
Common Roadblocks when Scraping
Although we have done a decent amount of scraping so far in the course, this is one of those topics that can depend very much so on the website we choose. Different websites present specific problems. Thus, in this section, we will discuss what are the most common problems that you will have to deal with and give you solutions and workarounds.
The Requests-HTML Package
This course is part of Module 4 of the 365 Data Science Program. The complete training consists of four modules, each building upon your knowledge from the previous one. Module 4 is focused on developing a specialized, industry-relevant skill set, and students are encouraged to complete Modules 1, 2, and 3 before they start this part of the training. Here, you will learn how to perform Credit Risk Modeling for banks, Customer Analytics for retail or other commercial companies, and Time Series Analysis for finance and stock data.See All Modules
Why Choose the 365 Data Science Program?
Real-life project and data. Solve them on your own computer as you would in the office.
Our expert instructors are happy to help. Post a question and get a personal answer by one of our instructors.
Earn a verifiable certificate after each completed course. Celebrate your successes and share your progress with your professional network!
Trust the other 500,000 students
The course is in-depth and is delivered at a steady pace with eye catching visuals. The instructors go through all the basics really well. They try not to over-simplify the material, you get a good sense аof how deep Data Science is in the course. Great job!!!
This course is amazing! After watching the video carefully and doing all the exercises, I am even capable of having discussions with Machine learning major Master’s students! High standard course with reasonable pricing.
Very clear and in-depth explanation of data science and how all the inter-related concepts apply in real life business environment. Absolutely great for beginners! Best data science course I have come across so far!
I would highly recommend the course to any beginner who wants to venture into the world of Data Science. The concepts are very well explained and there is an emphasis on practical application which really helps create a better understanding of the concepts.