Duration
12h Th, 26h Pr
Number of credits
| Master in agricultural bioengineering (120 ECTS) | 4 crédits | |||
| Master in bioengineering : chemistry and bio-industries (120 ECTS) | 4 crédits | |||
| Master in environmental bioengineering (120 ECTS) | 4 crédits | |||
| Master in forests and natural areas engineering (120 ECTS) | 4 crédits |
Lecturer
Yves Brostaux, Juan Antonio Fernandez Pierna, Hélène Soyeurt
Coordinator
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course is divided into 6 learning modules including one face-to-face session and e-learning activities:
- Module 1: Linear, Ridge and Lasso regressions
- Module 2: Principal component regression (PCR) + Partial least square regression (PLS)
- Module 3: Logistic regression
- Module 4: Random forest
- Module 5: PLS - discrniminant analysis + Super vector machine (SVM)
- Module 6: Neural network
Learning outcomes of the learning unit
After this course, the student will be able to conduct a complete exploratory data analysis from the data cleaning to the practical implementation.
The student will be also able to communicate the obtained results to stakeholders.
Prerequisite knowledge and skills
STAT2002-A-a : Statistique fondamentale, 1ère partie
STAT2004-A-a : Statistique appliquée : 1ère partie
STAT2005-A-a : Statistique appliquée : 2ème partie
STAT1213-A-a : Analyse statistique à plusieurs variables
Planned learning activities and teaching methods
The course is composed of 6 modules as aformentionned. Each module includes:
- one face-to-face session (2h) developping the theoritical concepts
- one e-learning session (1h) applying in practice the exposed theoritical concepts
- one e-learning session (3h) based on the resolution of a full data analysis dedicated to the exposed theoritical concepts
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face session (30%) + e-learning activities (70%)
Recommended or required readings
The course is given in full English.
All course supports are available on e-campus platform.
Exam(s) in session
Any session
- In-person
oral exam
Written work / report
Additional information:
The evaluation during the exam session will consist of:
- answering questions related to the course content (30 min)
- an oral assessment related to the work given one month before the evaluation (15 min).
Work placement(s)
Organisational remarks and main changes to the course
Contacts
Hélène Soyeurt
Chargé de cours
081/62.25.35
hsoyeurt@uliege.be