CB1: To show enough skills and knowledge in an area that, although grounded on high school and mostly learnt from textbooks, also includes the forefront advances of the field.
CE1: Ability to solve mathematical problems arising in Data Science and Engineering. Skills to apply knowledge on: Algebra, Geometry, Differential and Integral Calculus, Numerical Methods, Numerical Algorithms, Statistics, and Optimization techniques.
CG2: To master basic scientific and technical matters so that the student can learn new methods and new technologies, and adapt to new situations.
CG4: Ability to solve technological, computer, mathematical, and statistical problems that might arise in Data Science and Engineering.
CG5: Ability to solve problems from different subjects that are expressed mathematically, using numerical algorithms and computational techniques.
CT1: Skills to communicate knowledge, either orally or in written reports, both in front a specialized as well as a nonspecialized audience.
CT4: To develop personal abilities such as initiative, responsibility, negotiation, emotional intelligence, etc., as well as to master enough calculation tools so as to be able to adapt to the technical requirements of any professional activity.
RA1: To adquire advanced knowledge and deeply understand both the theoretical and practical aspects of typical Data Science and Engineering methods, even those at the forefront of the discipline.
RA2: To be able to apply their knowledge and know-how -- as well as to provide their own arguments or procedures -- to complex problems arising in professional and specialized domains requiring creative and innovative ideas.