Computer simulation and data science are the professions of the future. During this course we focus on the most advanced applications used to understand complex systems in broad areas including natural and physical sciences, social sciences, life sciences and management of (big) data. The students will have the opportunity to understand how to develop and apply high performance methods for numerical simulations used to solve complex problems related to time series analysis, modeling of real-life phenomena and computational medicine. A large part of the course is dedicated to data science and how to use data storage and data analysis in a smart way. Participants will learn various process discovery algorithms and the key analysis techniques in traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. The course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains.
A basic understanding of programming and statistics (at the undergraduate level) is assumed.
No required texts. Notes of the course. The lectures are designed to be self-contained.