Prof. Reza Arghandeh is the leader of the Data Science Group and the director of the Connectivity, Information & Intelligence Lab (Ci2Lab.com) at the Western Norway University of Applied Sciences (HVL), Bergen, Norway. He is also a Lead Data Scientist with StormGeo, an international weather insight company. He was an assistant professor from 2015 to 2018 in the Electrical and Computer Department at Florida State University, USA. Prior to FSU, he was a postdoctoral scholar at the University of California, Berkeley, EECS Dept 2013-2015. He completed his Ph.D. in Electrical Engineering at Virginia Tech. His research interests include spatiotemporal data analysis and computer vision for infrastructure networks. His research has been supported by the U.S. National Science Foundation, the U.S. Department of Energy, the European Space Agency, the European Commission, and the Research Council of Norway.
Abstract: Unlock the potential of data-driven decision-making with our crash course on Applied Causal Inference. Dive into the transformative world of causal inference and gain essential knowledge and practical skills to navigate complex causal relationships within your data. This crash course introduces foundational principles behind causal inference, including interventions, directed acyclic graphs, and structural causal models through a dynamic blend of lectures, real-world case studies, and hands-on exercises. Whether in economics, engineering, healthcare, or social sciences, this course empowers you to ask critical questions and solve complex problems confidently. This crash course focuses on practicality and provides some necessary Python libraries to apply causal inference techniques in your field. Explore causal relationships, identify hidden insights, and make informed decisions that drive meaningful outcomes.