Checking date: 31/05/2022


Course: 2022/2023

Visualization techniques for Big Data
(18196)
Study: Bachelor in Computer Science and Engineering (218)


Coordinating teacher: ONORATI , TERESA

Department assigned to the subject: Department of Computer Science and Engineering

Type: Electives
ECTS Credits: 3.0 ECTS

Course:
Semester:




Skills and learning outcomes
Description of contents: programme
1. Sense making and situational awareness in the Big Data era 2. Visual analytics: history, definition and development process 3. HCI principles: perception and interpretation, cognitive issues, semiotics and creativity 4. Interaction with visual and multi-modal interfaces 5. Processing temporal and geographic data 6. Applications of visual analytics
Learning activities and methodology
* Lectures: 1 ECTS. They aim to achieve the specific cognitive competencies of the subject and the transversal competencies of analysis and abstraction. * Practical classes: 1 ECTS. They aim to develop the specific instrumental competencies and the transversal competencies problem solving and application of knowledge. * Case study: 0,5 ECTS. Started during the practical classes and completed outside of them, it aims to complete and integrate the development of all specific and transversal competencies with the design and implementation of a case study through group work. * Tutorials: TUTORIALS. Individual or group tutoring sessions organized by the teacher for the students. * Final exam: 0,5 ECTS. It aims to influence and complement the development of specific cognitive and procedural skills. It reflects especially the use of the lectures.
Assessment System
  • % end-of-term-examination 20
  • % of continuous assessment (assigments, laboratory, practicals...) 80
Calendar of Continuous assessment

The course syllabus may change due academic events or other reasons.