Main Field of Study and progress level:
Computing Science: Second cycle, has only first-cycle course/s as entry requirements
Computational Science and Engineering: Second cycle, has only first-cycle course/s as entry requirements
Grading scale: TH teknisk betygsskala
Responsible department: Department of Computing Science
Contents
The focus of the course includes the acquisition of: knowledge of the foundations for classification and pattern recognition, basic knowledge of algorithms such as discriminant analysis, neural networks, k-nearest-neighbours and tree based algorithms, knowledge of and skills in solving real classification problems and developing system for decision support with application areas in industry and health care, skills in using tools for the design, development and integration of intelligent systems.
Required Knowledge
Univ:To be admitted you must have 60-ECTS credits in Computing Science or 2 years completed studies, in both cases including Scientific Computing 7,5 ECTS, (5DV005), Statistics for Computer Scientists 7,5 ECTS, (5MS005) and Data Structures and Algorithms 7,5 ECTS, (5DV043) or equivalent.
English proficiency equivalent to IELTS Academic Training minimum score 5.0 with no individual score below 4.5 (Tests taken before January 2005 not admissible or TOEFL minimum score 500 on paper based test and not below 4.0 on the TWE, Alternatively 173 on computer based test with iBT61 is also required as well as basic entrance requirements for higher studies in Swedish language proficiency if the course in taught in Swedish.
English proficiency equivalent to IELTS Academic Training minimum score 5.0 with no individual score below 4.5 (Tests taken before January 2005 not admissible or TOEFL minimum score 500 on paper based test and not below 4.0 on the TWE, Alternatively 173 on computer based test with iBT61 is also required as well as basic entrance requirements for higher studies in Swedish language proficiency if the course is taught in Swedish.
Literature
Valid from:
2009 week 45
Eklund Patrik Soft Computing : Edition for course at Umeå University, 2009
