Itsik Peer

Itsik Pe’er is an associate professor in the Department of Computer Science. His laboratory develops and applies computational methods for the analysis of high-throughput data in germline human genetics. Specifically, he has a strong interest in isolated populations such as Pacific Islanders and Ashkenazi Jews. The Pe’er Lab has developed methodology to identify hidden relatives — primarily in such isolated populations — that involves inferring their past demography, detecting associations between phenotypes and genetic segments co-inherited from the joint ancestors of hidden relatives, and establishing the exceptional utility of whole-genome sequencing in population genetics. With the arrival of high-throughput sequencing methods, Pe’er has focused on characterizing genetic variation that is unique to isolated populations, including the effects of such variation on phenotype.

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Machine Learning for Data Science and Analytics (edX) EdX
Columbia University,ColumbiaX

Machine Learning for Data Science and Analytics (edX)

Dive into the fascinating world of Machine Learning with our edX course, tailored for both novices and experienced professionals seeking to enhance their Data Science and Analytics capabilities. This course unravels the principles behind machine learning algorithms and their pivotal role in various applications such as web search, ad placement, credit scoring, stock trading, and more.

Self Paced
Self-Paced
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