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Data

Perform an Exploratory Data Analysis

Identify patterns in your data using PCA (Principal Component Analysis), a dimensionality reduction technique, and two of the most popular clustering methods: k-means and hierarchical clustering.
DifficultéMoyenne10 heures
Ce cours en libre accès vous intéresse ?

Do you have a large volume of data with multiple variables? Then you need to learn how to perform a multivariate exploratory analysis.

In this course, we will examine ways to efficiently analyze your data using techniques such as Principle Component Analysis, or PCA, which allows you to reduce the number of variables in your dataset while minimizing the amount of information lost. 

We will also look at two of the most popular Clustering Methods: the k-means algorithm and hierarchical classification. These enable you to group individuals according to their similarities.  

By the end of this course, you will understand when and how to apply these powerful analytical methods to your data.

Objectifs pédagogiques

  • Carry out a principal component analysis

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Contributeurs

Professeur

Llewelyn Fernandes

Founder of Think Create Learn (@tcreatelearn), helping young people and career changers build skills in data, AI, robotics, and programming.

Créé par

Mis à jour le 23/01/2025

Licence

Data

Perform an Exploratory Data Analysis

DifficultéMoyenne10 heures
Cours en libre accès