* General competences
- CG1: Adequate knowledge and skills to analyse and synthesise basic problems related to engineering and data science, solve them and communicate them efficiently.
- CG4: Ability to solve technological, computational, mathematical and statistical problems that may arise in engineering and data science.
- CG5: Ability to solve mathematically formulated problems applied to different subjects, using numerical algorithms and computational techniques.
- CG6: Synthesise the conclusions obtained from the analyses carried out and present them clearly and convincingly, both written and orally.
* Transversal competences
- CT1: Ability to communicate knowledge orally and in writing, before a specialised and non-specialised public.
* Specific competences
- CE1: Ability to solve mathematical problems that may arise in engineering and data science. Ability to apply knowledge about: algebra; geometry; differential and integral calculation; numerical methods; numerical algorithm; statistics and optimisation.
- CE2: Properly identify problems of a predictive nature corresponding to certain objectives and data and use the basic results of regression analysis as the basic basis of prediction methods.
- CE5: Understand and handle fundamental concepts of probability and statistics and be able to represent and manipulate data to extract meaningful information from them.
- CE7: Understand the basic concepts of programming and ability to carry out programs aimed at data analysis.