Study Programmes 2017-2018
MATH2021-1  
High-dimensional data analysis
Duration :
15h Th, 10h Labo., 15h Proj.
Number of credits :
Master in data science (120 ECTS)3
Master in data science and engineering (120 ECTS)3
Lecturer :
Gentiane Haesbroeck
Language(s) of instruction :
English language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Learning unit contents :
The theoretical course is devoted to the following themes:
- Multivariate exploratory data analysis - Principal component analysis - Clustering - Regularisation techniques - Multivariate ranks and quantiles
Learning outcomes of the learning unit :
The student will gain sufficient knowledge to be able to select the appropriate multivariate technique to reduce the dimension of the problem or construct classification rules,...
Prerequisite knowledge and skills :
A strong background in univariate statistics is required. Moreover, even though the mathematical justifications are not developped in details, the students must be familiar with the basic notions of linear algebra (vector, matrix, detemrinant, eigen valeurs and eigen vectors...).
Planned learning activities and teaching methods :
Practicals include data analysis with the statistical package R.
Mode of delivery (face-to-face ; distance-learning) :
The course is officially scheduled on Wednesday PM in the first semester. A more detailed planning will be distributed at the beginning of the lectures. 
Recommended or required readings :
There are no lecture notes. The slides will be available from eCampus. Moreover, for each them, a reference book will be notified in order to suggest additionnal reading.
 
Assessment methods and criteria :
The final grade is a weighted mean computed on the grades obtained for the personal homeworks given during the semester and fpr the exam consisting of a data analysis to be performed in the computer room.
Work placement(s) :
Organizational remarks :
The lectures are taught in English.
Contacts :
Lecturer: Gentiane HAESBROECK, Institute of Mathematics (B37), g.haesbroeck@ulg.ac.be