Number of hours
- Lectures 12.0
- Projects -
- Tutorials 12.0
- Internship -
- Laboratory works -
- Written tests 2.0
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)
- General overview about descriptive statistics
- Multidimensional Data
- Principal Component Analysis
- Discriminant Analysis
“Statistics” module (7th semester)
Test
50 % CC + 50 % final exam
Final exam conditions :
- 1 oral presentation in pairs (15 min presentation + 15 minutes questions)
- Oral presentation with digital material prepared in advance in class and at home
- Personal computer authorized
- Mobile phone and smartwatch forbidden
- Third time: adapted subject
CC requirements:
- MCQ
- Practice work's reports
- Oral presentation
Calendar
The course exists in the following branches:
- Curriculum - E2I - Semester 10
Additional Information
Course ID : KAELXM12
Course language(s): 
You can find this course among all other courses.