Skriv ut | Lukk vindu |
Vår 2021
DTE-3608 Artificial Intelligence and Intelligent Agents - Introduction - 5 stp
The course is administrated by
Type of course
Course contents
- 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
Application deadline
Admission requirements
A relevant undergraduate bachelor Engineering programme with minimum 30 credits Mathematics/statistics topics.
Application code: 9371
Objective of the course
After passing this course the student should have obtained the following learning outcome:
Knowledge
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
Skills
The student should be able to;
- To program basic AI and machine learning algorithms
- Create simple diagnosis, prediction, classification and recommendation systems
General Competence
- 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.
Language of instruction
Teaching methods
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
Assessment
Written examination, only simple calculator allowed during the exam.
Letter grading A - F, where F is fail grade.
There will be arranged a re-sit exam for this course.
Date for examination
The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.