Python Web Crawling & Automation to Do My Work (feat. Stock, Real Estate Data / Instagram)
In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.
[20% discount on all classes] Celebrating 4,000 cumulative students
Hello. This is Deepingsauce, Infraon knowledge sharer.
The cumulative number of students we announced at the start of summer, 3,000, has increased to 4,000 as summer draws to a close in the last month of August!
To thank you for your warm support, we have prepared a 20% discount event for all lectures to celebrate the 4,000th person milestone, just like last time (until 23:59 on August 31, 2021)
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1. Python that anyone can learn, whether they are a liberal arts student or a non-major!
2. Python Web Crawling & Automation to Replace My Work (feat. Stock, Real Estate Data / Instagram)
3. Data-based stock quant investment with Python Part 1
I hope that through this opportunity, we can further improve the quality of life of our students at a slightly lower price.
Also, there have been many inquiries about the second class of the existing 'Data-based Stock Quant Investment with Python' course, 'Part 2', and it will be opened in September at the earliest or October at the latest.
We would like to once again express our gratitude to the students who have been waiting for a long time. We ask for your interest and anticipation as we have prepared better quality content than the previous lectures to compensate for the delay.
thank you