Executive Data Science Capstone
Lead a virtual data science team at Zillow in this hands-on simulation, making key decisions to manage a complex analysis project.
Lead a virtual data science team at Zillow in this hands-on simulation, making key decisions to manage a complex analysis project.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Executive Data Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Lead and manage virtual data science teams
Make strategic decisions in complex analysis projects
Apply executive data science principles to real scenarios
Develop and deliver professional project presentations
Navigate real-world data science challenges
Skills you'll gain
This course includes:
0.5 Hours PreRecorded video
1 quiz
Access on Mobile, Tablet, Desktop
FullTime access
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There is 1 module in this course
This capstone project challenges participants to apply their executive data science knowledge in a realistic simulation developed with Zillow. Students take on the role of a data science team leader, making critical decisions throughout a complex analysis project. The course focuses on practical leadership scenarios, requiring participants to manage virtual team members, handle project challenges, and deliver final presentations that demonstrate their ability to lead data science initiatives effectively.
Executive Data Science Capstone
Module 1 · 2 Hours to complete
Instructors
Chief Data Officer and J Orin Edson Foundation Chair at Fred Hutchinson Cancer Center
Dr. Jeff Leek serves as the Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics in Public Health Sciences at the Fred Hutchinson Cancer Center. Previously, he was a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. He earned his PhD in Biostatistics from the University of Washington and is known for his significant contributions to genomic data analysis and statistical methods for personalized medicine. His research has advanced our understanding of molecular mechanisms related to brain development, stem cell self-renewal, and immune responses to trauma, with findings published in top scientific journals such as Nature and Proceedings of the National Academy of Sciences. Dr. Leek developed a highly acclaimed Data Analysis course for Biostatistics students at Johns Hopkins, which has consistently received teaching excellence awards. He is also recognized for his efforts in creating educational initiatives that leverage data science for public health and economic development, including massive open online courses that have engaged millions worldwide.
Professor of Biostatistics at Johns Hopkins University
Dr. Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and serves as a Co-Editor of the Simply Statistics blog. He earned his PhD in Statistics from the University of California, Los Angeles, and is recognized for his research in air pollution, health risk assessment, and statistical methods for environmental data. In 2016, he received the Mortimer Spiegelman Award from the American Public Health Association, honoring his significant contributions to health statistics. Dr. Peng developed the Statistical Programming course at Johns Hopkins to equip students with essential computational tools for data analysis. Additionally, he is a national leader in promoting reproducible research practices and serves as the Reproducible Research editor for the journal Biostatistics. His interdisciplinary research has been published in prestigious journals, including the Journal of the American Medical Association and the Journal of the Royal Statistical Society. He has authored over a dozen software packages that implement statistical methods for environmental studies and reproducible research, and he regularly conducts workshops and tutorials on statistical computing and data analysis.
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4.7 course rating
1,551 ratings
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