In this subject we intend to provide students with a practical knowledge of the basic methods of optimization that help to solve problems related to Data Science and Engineering. To this end, special emphasis will be placed on modeling optimization problems and on linear and integer programming and network optimization problem-solving techniques. Fundamentally, R and Python programming languages will be used.
Contingency plan
1. Modifications in the contents
There will be no modifications in the contents.
2. Methodologies
*Teaching methodologies are maintained
All teaching methodologies are maintained (master session, problem solving, tutored work and personalized attention).
*Teaching methodologies that are modified
There will not be any modification
3. Mechanisms of personalized attention to the students
- E-mail: It will be used daily for consultations and to request virtual meetings to solve doubts.
- Teams: There will be 2-3 weekly sessions for tutorials or virtual classes.
- Moodle: It will be used approximately twice a week to provide students with the material.
4. Modifications in the evaluation
There will be no modifications in the evaluation, except that this will be done using the Moodle and Teams tools.
*Evaluation observations
5. Modifications to the bibliography or webgraphy There will be no modifications.
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.
Subjects
