Today, we have access to an unprecedented amount of data. Historical data can be combined with machine learning techniques to create very accurate predictive models. Both data and machine learning are the main driving forces of the tech-celeration that we have witnessed in the recent years.
This class will provide a hands-on introduction to data science and machine learning topics, exploring areas such as data acquisition, regression, classification, clustering, association rules, recommender systems, neural networks, graph analytics, etc.
During the labs, we will use Colab and Python, and related libraries, to apply the concepts that we introduce during the lectures.
- Professor: Caroline Perrot
- Professor: Michail Vlachos
- Teacher: Angelina Frolova
