1. Students should be able to demonstrate they have acquired and understood the knowledge associated to an area that starts from high school education and reach a level that although it is based on text books, it also includes aspects that include concepts coming from up-to-date knowledge in the referread area.
2. Students should be able to apply the acquired knowledge to their job in a professional way and should incorporate the required competences that can be shown through solid arguments and the resolution of problems within their area of study.
3. Ability to design solutions based on automatic knowledge within applications applied to specific domains such as: recommendation systems, natural language processing, the WEB or online social networks.
4. Ability to develop web and mobile applications and crawlers to collect data using them.
5. Ability to develop data visualization tools to communicate the results derived from data analysis.
6. Adequate knowledge and skills to analyze and synthesize basic problems related to engineering and data science, solve them and communicate them efficiently
7. Ability to solve problems with initiative, decision making, creativity, and to communicate and transmit knowledge, skills and abilities, understanding the ethical, social and professional responsibility of the data processing activity. Leadership capacity, innovation and entrepreneurial spirit
8. Ability to communicate knowledge orally and in writing to both specialised and non-specialised audiences
9. Students should have acquired advanced knowledge and demonstrated an understanding of the theoretical and practical aspects and working
methodology in the field of data science and engineering with a depth that reaches the forefront of knowledge
10. Be capable of applying their knowledge and problem-solving skills, through arguments or procedures developed and sustained by themselves, in
complex or professional and specialized work settings that require the use of creative and innovative ideas.
11. Have the ability to collect and interpret data and information on which to base their conclusions including, where appropriate and pertinent, reflection on issues of a social, scientific or ethical nature within their field of study