Parallel Programming
Objectives
- To introduce the student in advanced methods of data analysis
- To present the field of intelligent data analysis as a novel research and application domain.
- To induce the necessity of intelligent data analysis methods by studying some relevant practical applications
- To offer the student the instruments that will allow him/her to develop different data analysis applications.
Class activities
All activities require physical class participation. This is a full attendance, not a distance learning program.
According to the National Education Act (1/2011), the recording of didactical activity by any means is only possible by explicit agreement of the teaching person. Consequently, no recording of any didactical activity, by any means and on any support, is allowed.
This is a research oriented class. Your grade will be based on your own work and on your understanding of it, including your ability to explain, defend and analyse your work and your results.
The students are invited to contact me individually, by email, at their own initiative, for lectures clarifications, explanations, consultations on class-relevant topics, research-relevant topics, or for required support or supervision for class-based activities.
Grading scheme
- 40% = Theoretical report
- 40% = Experimental report
- 20% = Exam paper