Course Decisions

  • Thread starter Thread starter sfeng
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11/19/16
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I am currently in my last term of my undergraduate degree and I was wondering if it would be more beneficial for me to take a statistics course in Time Series and Forecasting or dedicate more of my time to learning more coding and programming languages such as C++, Python and Matlab? The course also uses R to teach ARMA and GARCH processes.

Thanks for the replies!
 
I am currently in my last term of my undergraduate degree and I was wondering if it would be more beneficial for me to take a statistics course in Time Series and Forecasting or dedicate more of my time to learning more coding and programming languages such as C++, Python and Matlab? The course also uses R to teach ARMA and GARCH processes.

Thanks for the replies!
take the classes and implemente the solutions in R AND Python.
 
Python would definitely help you. I remember this course which I think can be helpful for you as it teaches Python keeping the trading perspective in mind and includes topics like time-series data with Python along with interactive coding exercises to practice.
 
I find Python more appealing bcoz of its countless features and flexibility. Since you're a UG, you should invest your time wisely. Go for the self-learning courses by some reputed and well known institutions (like the likes of Quantra) that offer short value-for-money courses, anytime learning, interactive exercises, self-learning videos, and much more.
  • For Python, you give this course a try.
  • For ARIMA and GARCH, you could check out this course.
  • And if you want to go for making a career in Algo Trading, learning from industry biggies like Dr. Ernest Chan, Nitesh Khandelwal, Dr. Thomas Starke, Euan Sinclair, and many more, go for the EPAT programme.

I hope this helps you out. I'd be delighted to learn of your experience and journey here. All the best!
 
You seem to be a big fan of Quantra. This is the 4th time in so many days that I have seen this name.
And one trader here on QN has never heard of you.
 
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