This is a rigorous class that will synthesize much of what you have learned in the past two years in the Data Science minor.
In particular, we will draw upon your existing knowledge in:
This class is taught in Python. We will assume that you are already comfortable using Numpy, Pandas, and Matplotlib.
By the end of this course, you will understand how the pieces fit together -- how statistics, computer science, and mathematics combine to make up the field of data science.
First, although some of you are enrolled in Dr. Dekhtyar's section and others are enrolled in Dr. Sun's, there is no difference between the two sections. You will all meet in a single section co-taught by both of us, and you will all be graded according to the same standards.
Dr. Sun and Dr. Dekhtyar have different lecturing styles:
The schedule for every lecture can be found on the Lectures page.
All coding will be done on JupyterHub. This means that you should not have to install any software to take this class.
Because there are two sections, Dr. Sun does not have the ability to e-mail students in Dr. Dekhtyar's section, nor does Dr. Dekhtyar have the ability to e-mail students in Dr. Sun's. To make communication easier, we will post all announcements on the Piazza forum. We will assume that all of you have an account on Piazza, or you may miss important communications from us.
Your overall grade will be calculated according to the following weighting scheme.
|3-4 Team Projects
|(Approximately) Weekly Assignments||10%|
|Goodfellow et al. Deep Learning. MIT
Available for free online.