Teaching GuideTerm
Faculty of Computer Science
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Grao en Ciencia e Enxeñaría de Datos
 Subjects
  Numerical Methods for Data Science
   Assessment
Methodologies Competencies Description Qualification
ICT practicals A2 B2 B3 B4 B9 B10 C1 C4 Several practical small projects will be proposed and evaluated along the course. 30
Supervised projects A2 B2 B3 B4 B7 B8 B9 B10 C1 C4 Teachers will propose a supervised project to each student that he/she will have to defend at the end of the subject. 20
Problem solving A2 B2 B4 B9 B10 During the course there will be some small tests. They will consist on solving problems of the same type as those studied during the classes. 20
Objective test A2 B2 B3 B4 B7 B8 C1 There will be a written exam on the dates set by the Faculty Board. 30
Collaborative learning A2 B2 B3 B4 B7 B9 B10 C1 The teacher will propose a supervised project that students will have to defend during the course. This project is optional and can be seen as an alternative to the supervised project. Therefore, it will count up to 20% of the final mark. 0
 
Assessment comments

In order to pass the subject, it is mandatory to attain at least a qualification of 50%.

In the extraordinary call there will be an objective test. It will not be possible to recover the part of the final mark corresponding to continuous assessment. 

Part-time students and those with academic dispensation of attendance exemption that have not been evaluated of ICT practicals can do a specific exam to recover 30% of the final mark; they can obtain 50% of the final mark with the objective test.

Fraudulent performance of the tests or evaluation activities, once verified, will directly imply a mark of "0" in the subject, invalidating any grade obtained in all the evaluation activities. 

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