In data science, data analysis and machine learning techniques are applied to visualize data, understand trends, and make predictions. In this course we learned how to obtain data, preprocess it, apply machine learning methods, and visualize the results. This course will provide enough theoretical knowledge, and enough skill with modern statistical programming languages and their libraries, to define and perform complete data science projects.
I had taken a couple data science classes before, so I had already been exposed to everything we covered in this class. That being said, I really like data science so I had a lot of fun here. We started going over numpy basics, and ended with decision trees. It would have been nice to go into more depth with some of the topics we covered, but it was nice to have a refresher either way.
We did a large project as a group to go through the process of finding, cleaning, and analyzing data. We looked at animal shelter data, and our end goal was to make a prediction on length of stay with a high level of accuracy. We used out of the box models from that we could train easily.
ChompingTheBit 