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Curso avanzado de Análisis de Datos con R y Matlab! (+9 horas!)
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Curso avanzado de Análisis de Datos con R y Matlab! (+9 horas!)

GRATIS199,99€Ofertas Udemy
Publicado el 04 de marzo

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Curso gratuito de Udemy por tiempo limitado con muy buenas valoraciones!
+9 horas de vídeo bajo demanda (en inglés, con la posibilidad de añadir subtítulos) en las que aprenderás:
Lo que aprenderás
  • Concepts related to Robust Statistics.
  • Performance of outlier detection methods.
  • Learn to differentiate one method from another.
  • Identify the most robust and efficient methods that you should use in practice.
  • Application of the methods with handmade examples.
  • Application of the methods with R and Matlab.

  • Basic statistical knowledge.

Robust data analysis and outlier detection are crucial in Statistics, Data Analysis, Data Mining, Machine Learning, Pattern Recognition, Artificial Intelligence, Classification, Principal Components, Regression, Big Data, and any field related with data. Researchers, students, data analyst, and mostly anyone who is dealing with real data have to be aware of the problem with outliers and they have to know how to deal with this issue.

This course is intended to study the characteristics of the problem, its consequences and learn how to recognise it through the existing approaches. We will deeply study the performance and the properties of the methods to detect outliers in case we have a single random variable (univariate data) or in case we have more than one (multivariate data) . We will see the theoretical properties of the methods and we will apply them to examples. In addition, we are going to see the practical performance with the software R and Matlab, and we will learn the different existing packages in both software for the problem of outlier detection. The implementation and example codes are available in the open Google Drive repository.

You will learn about both classical and recent algorithms for outliers detection:

Univariate space:

Method SD
Z score
Tukey Boxplot
Modified Z score
Adjusted boxplot

Multivariate space:

Classical Mahalanobis distance
Robust Mahalanobis distance
Adjusted MCD

Linear regression:

Ordinary least squares (classic method)
Robust regression: LAD, LMS, LTS

In addition, we have two sections of basic concepts that will help you to remember some notions necessary to understand the methods for outlier detection.

Basics I

Sample, population, random variable
Distribution of a random variable
Normal distribution
Fisher chi-square, t-student and F distributions

Basics II

Linear algebra
Multivariate variable
Joint and marginal distribution
Independence, covariance and correlation
Multivariate Normal
With this course you will master one of the most important issues today both academically, as in industry and in data analysis. The examples will help you to visualize this importance and as a guide to carry out these analyzes by yourself.

¿Para quién es este curso?
  • Data scientist.
  • Data analyst.
  • Students.
  • Researchers.
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7 comentarios
Me sale a pagar 18,99
Aguttii04/03/2020 14:13

Me sale a pagar 18,99

Pues no debería, está gratis durante 2 días.
muchas gracias compi!!
"The coupon code entered is not valid for this course. Perhaps you used the wrong coupon code?"

Se habrán acabado YA los 3 dias!?!?!?! Que pena!
luisgal05/03/2020 11:41

"The coupon code entered is not valid for this course. Perhaps you used …"The coupon code entered is not valid for this course. Perhaps you used the wrong coupon code?"Se habrán acabado YA los 3 dias!?!?!?! Que pena!

Parece que sí, que se ha acabado la oferta.
En ocasiones supongo que lo limitan a número de inscripciones, por lo que si se llena el cupo automáticamente el cupón deja de estar disponible antes de los 3 días en este caso.
Una pena, gracias por avisar, saludos
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