Introduction To Data Science (Udemy.com)
Use the R Programming Language to execute data science projects and become a data scientist.
Created by: Nina Zumel
What you will learn
- Start and execute the steps of a data science project, from project definition to model evaluation.
- Use machine learning techniques to build effective predictive models.
- Learn how to find and correct common problems found in real world data.
Quality Score
Overall Score : 84 / 100
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Instructor Details
- 4.2 Rating
- 50 Reviews
Nina Zumel
Nina Zumel, PhD, has over 10 years of experience in research, machine learning, and data science. She is a co-author of the popular book Practical Data Science with R, co-author of the EMC data scientist certification program, and blogs often on statistics, data science, and data visualization. I am principal at with the data science consulting firm Win-Vector LLC. Win-Vector LLC specializes in data science research, implementation, and training. I have over 10 years of experience in research, teaching, machine learning, and data science.
I am co-author of the popular book Practical Data Science with R, and I blog often on mathematics, programming, machine learning, and optimization on the Win-Vector blog.
My profesional experience includes managing a data science group for Shopping dot com (an eBay company), working in price optimization for Rapt (acquired by Microsoft), and apply machine learning at a web-scale for Kosmix (acquired by Walmart online). My original fields of study were mathematics (AB UC Berkeley) and computer science (Ph.D. Carnegie Mellon) with a heavy emphasis on probability theory.
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