This class explores key climate questions through data. Students will learn to collect, clean, and analyze data, apply causal methods using Python, and communicate insights clearly. With a focus on sustainability, the course builds skills to avoid pitfalls ...
The students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, major algorithmic paradigms such as dynamic programming, s ...
Hands-on introduction to data science and machine learning. We explore recommender systems, generative AI, chatbots, graphs, as well as regression, classification, clustering, dimensionality reduction, text analytics, neural networks. The course consists o ...
Machine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
The objective of this course is to provide the necessary background for designing efficient parallel algorithms in scientific computing as well as in the analysis of large volumes of data. The operations considered are the most costly steps at the heart of ...
This class provides a hands-on introduction to data science and machine learning topics, exploring areas such as data acquisition and cleaning, regression, classification, clustering, neural networks, and visualization. The course consists of lectures and ...