Python for Analytics

Python started out as a general purpose language when it was created in 1991 by Guido van Rossum. It was embraced early on by Google founders Sergei Brin and Larry Page (“Python where we can, C++ where we must” was reputedly their mantra).

In 2006, van Rossum (right) went to work at Google, where he was permitted to spend half his time on further development of Python (he now works at Dropbox). It is no surprise, therefore, that Python now stands as a popular software environment for analytics.

Python is typically used in a deployment setting when speed and performance are essential, and also when powerful data handling capabilities are needed (R, by contrast, offers more in the way of statistical modeling tools, and is often preferred in the model development phase). Here at Statistics.com we use Python in a number of our more advanced courses – Text Mining, Anomaly Detection, Deep Learning, and more. If you have some programming experience (e.g. with R) and you’d like to add Python to your tool set, you’ll be interested in:

May 11 – Jun 8: “Introduction to Python for Analytics“

This is also a required course in our Programming for Data Science PASS Certificate Program.

Your instructor is David Masad, a Presidential Scholar at George Mason University. He will answer your questions and comments on a regular basis throughout the course on a private discussion forum.

The course takes place online at Statistics.com in a series of weekly lesson and assignments and requires about 15 hours/week. Participate at your own convenience; there are no set times when you are required to be online.