Data-driven stock quant investment with Python Part 1
In this class, you will learn about the principles and methods of analyzing and processing various types of financial data using Python's Pandas library, apply them to situations you may encounter in the real world, and ultimately learn how to implement backtesting based on financial statement data (based on Kang Hwan-guk's book, "You Can Do Quant Investment"). As a result, you can break away from being a "passive investor" who simply follows what others say without verifying or basing the investment logic, and become a "self-directed and active investor" who can freely extract various elements necessary for strategy implementation from data and quantitatively analyze them using Python and Pandas.
1,849 learners
Level Basic
Course period Unlimited
[20% off all lectures] Invest smartly with Python in the new year!
Hello. This is Deepingsauce, Infraon knowledge sharer.
As 2021 has been a year and the new year has seen more and more people show interest in our classes, we have surpassed 6,500 cumulative students.
To thank you for your warm support and to help you achieve your goals with Python in the new year, we have prepared a 20% discount event for all lectures : From Monday, January 10, 2022 to Sunday, January 16, 2022 (for one week )
Go to course
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
4. Data-based stock quant investment with Python Part 2
I hope that through this opportunity, we can further improve the quality of life of our students at a slightly lower price.
* Additionally, the following event has been prepared, so for those who have been interested in my classes, this will be a great opportunity to take them at a low price.
1. Class SNS sharing event (up to 30%)
2. Bundle Course Discount: 30% discount on all courses when purchasing the entire curriculum on the Roadmap page
Happy New Year. Thank you.