Stochastic Processes: Data Analysis and Computer Simulation

Обучение бесплатное
Сертификация платная
10 месяцев
О курсе

The motion of falling leaves or small particles diffusing in a fluid is highly stochastic in nature. Therefore, such motions must be modeled as stochastic processes, for which exact predictions are no longer possible. This is in stark contrast to the deterministic motion of planets and stars, which can be perfectly predicted using celestial mechanics.

This course is an introduction to stochastic processes through numerical simulations, with a focus on the proper data analysis needed to interpret the results. We will use the Jupyter (iPython) notebook as our programming environment. It is freely available for Windows, Mac, and Linux through the Anaconda Python Distribution.

The students will first learn the basic theories of stochastic processes. Then, they will use these theories to develop their own python codes to perform numerical simulations of small particles diffusing in a fluid. Finally, they will analyze the simulation data according to the theories presented at the beginning of course.

At the end of the course, we will analyze the dynamical data of more complicated systems, such as financial markets or meteorological data, using the basic theory of stochastic processes.

Stochastic Processes: Data Analysis and Computer Simulation
The course deals with how to simulate and analyze stochastic processes, in particular the dynamics of small particles diffusing in a fluid.
Что Вы изучите?
  • Basic Python programming
  • Basic theories of stochastic processes
  • Simulation methods for a Brownian particle
  • Application: analysis of financial data
Ryoichi Yamamoto
Ryoichi Yamamoto
Professor, Chemical Engineering Kyoto University
Ryoichi was born in Ishikawa Prefecture, Japan in 1965. He obtained his B. Eng. (1988) and M.Eng. (1992) degrees from Kobe University and Ph.D. (1996) degree from Kyoto University. He was a research associate at Kobe University (1994-1996), a research associate (1996-1999) and a lecturer (2000-2004) at the Department of Physics, Kyoto University, an associate professor at the Department of Chemical Engineering, Kyoto University (2004-2008). Since 2008, he has been a professor there. He works on dynamical problems of soft matters (complex fluids, glasses, polymers, and colloids) and active matters (micro-swimmers and cells) by developing and using novel methods of computer simulations suitable for those systems.
John J. Molina
John J. Molina
Assistant Professor Kyoto University
John was born in Bogota, Colombia in 1983. He obtained his B.s Sci. from the Andes University (2007), M. Sci. from the ENS-Lyon (2008), and Ph.D. from the University of Paris 6 - UPMC (2011). He joined Kyoto University as a research fellow in 2011, and since 2014 he is an assistant professor in the Department of Chemical Engineering. He is focused on studying the dynamics of soft-matter systems using computer simulations.
Эта платформа предоставляет все курсы бесплатно. Авторами выступают топовые университеты и корпорации, которые стараются удерживать стандарты качества. За несоблюдение дедлайнов, невыполнение домашнего задания студенты теряют баллы. Как и в других платформах, лекционные видео чередуются с практическими заданиями. Обучение проводится на английском, китайском, испанском, французском и хинди.