DTE-3608 Artificial Intelligence and Intelligent Agents - Introduction - 5 ECTS
- The students will be introduced to AI as a discipline and scientific research areas and understand its industrial and societal impact
- The student will be introduced to an array of basic methods illustrating the different fields of AI and machine learning
- A selection of decision and machine algorithms will be presented in depth and compared to each other
- The subject of information management and decision theory with scarce or corrupted data will be treated.
- The course will also introduce agents, agent architectures and agent learning for individual as well as colonies and groups
After passing this course the student should have obtained the following learning outcome:
The student shall have;
- An overview of the field of Artificial Intelligence and its applications
- Knowledge of symbolic methods, knowledge representation, knowledge engineering, simple fuzzy systems and learning methods like sequential covering
- Knowledge of how to deal with incomplete, scarce and qualitative data
- Knowledge of numerical methods including perceptron based neural networks, basic genetic algorithms.
- Basic understanding of classification, clustering and regression methods
The student should be able to;
- To program basic AI and machine learning algorithms
- Create simple diagnosis, prediction, classification and recommendation systems
- The student will be able to contribute effectively in industrial AI and machine learning projects
- The student will have sufficient knowledge to pursue self-studies in specific AI and machine learning topics.
40 hours of lectures and hands-on class exercises
30 hours of self-study exercises with guidance to be handed in for approval
Lectures will be held in English (Provided the presence of English speaking students, English will be chosen).
Lecture notes will be given in English.
Written examination will be in English
- About the course
- Campus: Narvik |
- ECTS: 5
- Course code: DTE-3608
- Responsible unit
- Institutt for datateknologi og beregningsorienterte ingeniørfag
- Tidligere år og semester for dette emnet