PHYS 247: Introduction to Applied Data Science
The course “Introduction to Applied Data Science” is designed to give students the necessary background knowledge to follow more advanced and specialized topics in data science. The course is designed to provide students with necessary background in statistics, linear algebra, probability theory, machine learning, big data tools, data visualization and Python programing. The course prepares students from different disciplines to take advanced and specialized data science courses.
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About the Instructor
Bahram Mobasher is Professor of Physics and Observational Astronomy at the University of California, Riverside (UCR). His main research is in formation and evolution of galaxies over the age of the Universe using large galaxy surveys. For his research Prof. Mobasher uses data from the ground-based and space telescopes- both imaging and spectroscopy. He is the Principal Investigator of a grant from NASA-MIRO program- Fellowship and Internship for Extremely Large Data Sets (FIELDS)- to train students in data science. He is leading collaborations in Data Science with NASA’s Jet Propulsion Laboratory (JPL). Prof. Mobasher is the co-founder of the multi-disciplinary Data Science Center at UCR. Prof. Mobasher has a BS in Physics. He obtained his MS and PhD in Observational Cosmology from Durham University, UK. He has an MS in optoelectronics and graduate diploma in Microwave engineering from the University of London. He was a research fellow in Astrophysics at the Imperial College, London. For seven years he was a staff scientist at the European Space Agency and an associate astronomer at the Space Telescope Science Institute, Baltimore, working on the calibration of instruments on the Hubble Space Telescope as well as doing research on the Hubble data.