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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.
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.
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.
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.
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.
In this short section, we will discuss an easy way to scrape HTML tables.
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.
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
Real-life project and data. Solve them on your own computer as you would in the office.
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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.