Introduction To Data Science (Udemy.com)

Use the R Programming Language to execute data science projects and become a data scientist.

( 50 Reviews )

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

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Qualified Instructor

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Course Depth & Coverage

Overall Score : 84 / 100

Instructor Details

Nina Zumel

4.2 Rating
50 Reviews

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.