- KAELXM12

Informations générales

  • Number of hours

    • Lectures 12.0
    • Projects -
    • Tutorials 6.0
    • Internship -
    • Laboratory works -
    • Written tests -

    ECTS

    ECTS 0.5

Goal(s)

The aim of this course is to familiarize you with high-dimensional datasets and to understand the issues involved in data processing.

We will look at two very classic methods of data analysis, one for reducing the number of variables and one for classifying observations.

The course is mainly conducted in the form of practices during which students work with Python on real data sets.

Content(s)

  1. General overview about descriptive statistics
  2. Multidimensional Data
  3. Principal Component Analysis
  4. Discriminant Analysis

Prerequisites

“Statistics” module (7th semester)

Test

100 % CC:

If this teaching unit is not validated, there will be no possibility of taking additional tests to validate it.

Calendar

The course exists in the following branches:

  • Curriculum - E2I - Semester 10

Additional Information

Course ID : KAELXM12
Course language(s): FR

You can find this course among all other courses.