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

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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.

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Reviews

4.2

50 total reviews

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By Simon Schweitzer on

Der Kurs bietet eine sehr schne Einfhrung bislang! Vielen Dank!

By Alejandro Soto Murillo on

es bastante basico, ya que mi formacin base es estadistica

By Andrei Poplaukhin on

This course is certainly not for beginners. So it cannot be an introduction to data science. You need to have strong foundation in R and statistics in order to be able to follow the course. I will get back to it, once I improve the other skills so I'll be able to take the most out of it.

By Raymond Balise on

The detail of NB are too much at this point. Working this out with a sentence would have helped.

By Abdulrahman Dallak on

That's a great course and it's well presented.

By Ryan Peugh on

Love having a video course taught by real experts in the field! I bought their book as well. It creates great synergy in learning to get the material presented quickly in video format and more in depth in the book.

By Csar Alejandro Lpez Santiago on

Buena eleccin, aunque en algunas secciones el audio no concuerda con los subtitulos.

By Alexandra maria rios cabral on

Estou procurando algo mais bsico como manipula�o de tabelas. Modelos estatsticos n�o s�o grande novidade pra mim. Mas tenho encontrado dificuldades em tornar a manipula�o de dados numa tabela algo mais simples e rpida.

By Nico Blijleven on

The modelling info was a bit to high. Hopefully it will become clearer during the course.

By Robert Stanfield on

Yes

By Luis Furlan on

A very good introduction! The delivery format tends to be a bit overwhelming at times...too much material in too little time...this is specially true when going into the R code, very hard to keep up.Overall, I'ld recommend the course to anyone interested in the topic.

By Fabio Amaral on

Very good introductory course. It gives a good flavour of what is like to work on real world data science projects and ways to address common issues faced along the way.