Previous subjects
The goals will focus on:
Diving into forecasting concept, firstly from the point of view of corporations and organisations and, afterwards, reviewing different forecasting techniques, specially for time series.
SYLLABUS
1. Need and use of forecasting in decision making
2. Time series and stochastic processes
3. Dynamic systems and models
4. Traditional forecasting techniques
5. Machine Learning for forecasting
6. Use cases
Note: Topics can be adjusted and/or modified at the discretion of the master's coordination.
The methodology used combines master classes, student participation, practical exercise at class and solving a challenge or doing a research exercise as final work. For the student, this will involve group work with an oral presentation at class and a written assessment.
This subject will be assessed on a continuous via the development of a challenge proposed or by a research work on already existing solutions in some scientific context and a final presentation in class.
Continuous assessment
This subject will be assessed on a continuous via the development of a challenge proposed or by a research work on already existing solutions in some scientific context and a final presentation in class.
The final grade will be a weighting of:
- Challenge solution (implementation) and/or presentation or research work: 80%
- Class participation: 20%
Extraordinary call
The exam and/or works of extraordinary call will be determined from the coordination of the subject.
Copies regulations
The subject is governed by the general regulations of copies of La Salle Campus BCN:
https://www.salleurl.edu/en/copies-regulation
The training activities will be considered to have the following category:
Final exercise or challenge: highly significant
The bibliography will be detailed throughout the course.
All class material (presentations, exercises, articles, documents, etc.) will be shared in the subject folder of the La Salle Intranet: eStudy.
Complementary bibliography will be detailed throughout the course.