Hello! We're glad you're signed up for the course, and we're furiously putting the final touches on it, as it launches officially.
There have been some questions about the scope of the course, so I wanted to take moment to cover some of those questions:
* This is an 8 week course, not 6 weeks as the site had shown before.
* This is a programming project-oriented course involving Python programming. At the end of the course you will have created a working market simulator that you can use to test your own investing strategies. On average you can expect to spend up to 5 hours per week on programming.
* Recommended Background: The course is pragmatic: We focus on what you need to know to analyze historical performance of portfolios and equities and how build the market simulator. We'll cover some of the pitfalls you might experience as you explore trading strategies. If you are already an experienced trader and are familiar with concepts like Mean Variance Optimization, you might not find this course challenging.
* Software you'll need: In order to complete the programming assignments you will need to become familiar with basic Unix commands, and you must download and install a set of Python modules to your computer (including NumPy, SciPy, Pandas, and QSTK). The software is supported on Unix (MacOS and Ubuntu Linux). If you would like to use a Windows PC, our recommendation is to install Ubuntu with a virtual environment such as virtualbox, vmware or parallels. For more information about installing the software you will need, visit http://wiki.quantsoftware.org/index...tallation_Guide
Sincerely,
Tucker Balch, Ph.D.
Georgia Institute of Technology
I took Computing for Data Analysis, it's an introductory course to R. It was really good. over 4 weeks, the professor did a great job of presenting some of the basics and things you'd want to do in R. They always say R has a steep learning curve, so I've always put it off. But this course got me over it, now I like using R.
For the Computational Investing, it looks like the first challenge will be getting his Python module installed and running. I may have to go with the virtual image of Ubuntu 11, but some people said it was slow. I have a Ubuntu 10.4 machine, but they say 11 or higher.
I took Computing for Data Analysis, it's an introductory course to R. It was really good. over 4 weeks, the professor did a great job of presenting some of the basics and things you'd want to do in R. They always say R has a steep learning curve, so I've always put it off. But this course got me over it, now I like using R.
For the Computational Investing, it looks like the first challenge will be getting his Python module installed and running. I may have to go with the virtual image of Ubuntu 11, but some people said it was slow. I have a Ubuntu 10.4 machine, but they say 11 or higher.
Was that R class the one from Washington U?
I'm setting up using virtual box if it turns out to be too slow I'll move to a full Ubuntu install.
I downloaded the qstk yesterday gonna instal today to c how it goes.
Why would you study in your spare time?
