Tools of Artificial intelligence / Kunstig intelligens værktøjer
The Maersk Mc-Kinney
Moller Institute, Odense
Teaching activity id: RMAI2-U1.
Teaching language: English.ECTS / weighting: 5 ECTS / 0.083 full-time equivalent.
Period: Spring 2016.Approved: 14-05-14.
Offered in: Odense.
Subject director:
Ole Dolriis, The Maersk Mc-Kinney Moller Institute.
Prerequisites:
Learning outcomes:
Lessons:
Form of instruction:
Evaluation
Programmes:
Master of Science in Engineering (Robot Systems)
2. semester, mandatory. Offered in: Odense
Teaching activity id: RMAI2-U1.
Teaching language: English.ECTS / weighting: 5 ECTS / 0.083 full-time equivalent.
Period: Spring 2016.Approved: 14-05-14.
Offered in: Odense.
Subject director:
Ole Dolriis, The Maersk Mc-Kinney Moller Institute.
Prerequisites:
Basic object oriented programming knowledge is recommended.
Learning outcomes:
Knowledge:
+ understanding of basic machine learning techniques: neural
networks, genetic algorithms and reinforcement learning
+ understanding of representational techniques appropriate to the
above learning methods
+ understanding of the experimental challenges and demands of the
machine learning approaches referred to above
Skills:
+ able to implement, debug and deploy the AI techniques taught in new
situations
+ able to devise suitable representations of data for chosen machine
learning techniques
+ able to test, evaluate and document the performance of chosen
machine learning techniques using suitable correct methodologies
+ able to write a straightforward experimental scientific paper
documenting a comparison experiment
Competences:
+ can identify robotic problems where machine learning techniques
could be applied
+ can select appropriate techniques from the toolbox of possibilities
+ able to characterise a new AI technique in terms of scope and
type (unsupervised, semi-supervised or supervised)
+ can evaluate reported applications of machine learning techniques
in terms of results and methodology
Lessons:
48 lessons
Form of instruction:
Lectures and exercises.
Evaluation
Individual written report based on project and evaluated according to the Danish 7-point grading scale with external co-examiner.
Programmes:
Master of Science in Engineering (Robot Systems)
2. semester, mandatory. Offered in: Odense