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Learning Systems

7,5 credits

The course aims at providing an overview of the field machine learning; learning and self-organizing systems for classification and prediction.

Upon completion of the course, the student shall be able to

  • judge when the methods introduced in the course is applicable
  • read and comprehend scientific material in the area
  • apply the methods on real world problems
  • assimilate and present scientific results in the learning systems area

Spring 2022 (Campus based, Halmstad, 50%)

Level:

Advanced level

Application code:

X3431

Entry requirements:

Bachelor of Science degree (or equivalent) in an engineering subject or in computer science. Courses in computer science, computer engineering or electrical engineering of at least 90 credits, including thesis. Courses in mathematics of at least 30 credits or courses including calculus, linear algebra and transform methods. The course Engineering mathematics 7.5 credits.

Selection rules:

Available for exchange students. Limited numbers of seats.

Start week:

week: 03

Instructional time:

Daytime

Language of instruction:

Teaching is in English.

Show education info
Spring 2023 (Campus based, Halmstad, 50%)

Level:

Advanced level

Application code:

X3431

Entry requirements:

Bachelor of Science degree (or equivalent) in an engineering subject or in computer science. Courses in computer science, computer engineering or electrical engineering of at least 90 credits, including thesis. Courses in mathematics of at least 30 credits or courses including calculus, linear algebra and transform methods. The course Engineering mathematics 7.5 credits.

Selection rules:

Available for exchange students. Limited numbers of seats.

Start week:

week: 03

Instructional time:

Daytime

Language of instruction:

Teaching is in English.

Show education info

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