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Dr. Peter Gedeck

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Dr. Peter Gedeck

Dr. Peter Gedeck

Peter Gedeck is at the forefront of the use of data science in drug discovery. He is a Senior Data Scientist at Collaborative Drug Discovery, which offers the pharmaceutical industry cloud-based software to manage the huge amount of data involved in the drug discovery process. Drug discovery involves the exploration and testing of huge numbers of molecule combinations, and much of that testing takes place analytically, hence the need for robust software to handle the data and provide a framework for analyzing it. Peter’s specialty is the development of machine learning algorithms to predict biological and physicochemical properties of drug candidates. Prior to this, he worked for twenty years as a computational chemist in drug discovery at Novartis in the United Kingdom, Switzerland, and Singapore. His research interests include the application of statistical and machine learning methods to problems in drug discovery. clinical research and meta-analysis. Peter is also a co-author of Data Mining for Business Analytics – Using Python, continuing this best-selling Wiley series, which serves as the foundation for Statistics.com’s Predictive Analytics series of courses.  Galit Shmueli and Inbal Yahav, fellow instructors at Statistics.com, are also co-authors in this book series, as is Peter Bruce, the founder of Statistics.com.

Statistics.com Instructor Since

January 2018

Education

  • MSc, Chemistry, University of Erlangen-Nürnberg in Germany and University College London in the United Kingdom
  • PhD Chemistry, University of Erlangen-Nürnberg in Germany
  • Mathematics, Fernuniversität Hagen, Germany

Publications

  • Author of publications in the area of drug discovery, computational chemistry, and cheminformatics. https://scholar.google.com/citations?user=qfijp7UAAAAJ

Awards

  • Fellowship of the German Academic Exchange Service (DAAD, 1987-1988)
  • Fellowship of the German Academic Scholarship Foundation (Studienstiftung des Deutschen Volkes, 1987-1991)
  • Doctoral fellowship of the German Academic Scholarship Foundation (1991-1995)

Courses Taught

Predictive Analytics 1 with Python - Machine Learning Tools
Predictive Analytics 2 with Python - Neural Nets and Regression
Predictive Analytics 3 with Python - Dimension Reduction, Clustering, and Association Rules
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About Statistics.com

Statistics.com offers academic and professional education in statistics, analytics, and data science at beginner, intermediate, and advanced levels of instruction. Statistics.com is a part of Elder Research, a data science consultancy with 25 years of experience in data analytics.

 The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV)

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