BAPD3000 Dynamic Project Leadership Course description

Students will work in groups (typically 2-3 students, max 5) on a project. The exam submission will be an individual written project report, 3000-4000 words documenting the project work. Students can work on a project individually at the discretion of the Course Coordinator.

The exam can be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

Ingen forkunnskapskrav.

Etter gjennomført emne har studenten følgende læringsutbytte, definert i kunnskap, ferdigheter og generell kompetanse.

Kunnskap

Studenten behersker dynamisk prosjektledelse herunder

• prosjektplanlegging
• budsjettkontroll
• jobbe i prosjektteam
• klientkontroll

Ferdigheter

Studenten kan

• kan koordinere eget prosjekt
• kan styre og vurdere økonomien i et prosjekt
• kan håndtere ledelsesaspekter i prosjektet - herunder oppgavefordeling og kompetansekrav
• kan håndtere konfliktsituasjon i prosjekter
• har kjennskap til løsning av kreativitetsblokader
• kan håndtere klienter

Generell kompetanse

Studenten kan

• lede et prosjekt
• forstå styrker og svakheter i prosjekter, reflektere over sin egen utvikling i læreprosessen og justere denne under veiledning

Grade scale A-F.

Gruppearbeid, workshop koordinert med 1. års-studenter og 2. års-studenter som arbeider i emnene BAPD1010 og BAPD2000.

Følgende arbeidskrav er obligatorisk og må være godkjent for å fremstille seg til eksamen:

• En oppgave.
• En rapport.

The course focuses on the application of artificial intelligence in user interfaces, techniques, technologies and ethical consequences.

No formal requirements over and above the admission requirements.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of this course the student has:

• specialized knowledge of artificial intelligence and machine learning techniques and technologies, and how they can be applied in intelligent user interfaces
• specialized knowledge practical application areas of intelligent user interfaces
• specialized knowledge about how intelligence and automation in user interfaces affects users

Skills

On successful completion of this course the student can:

• assess the need for and feasibility of applying artificial intelligence and machine learning to a given user interface problem
• identify suitable artificial intelligence or machine learning techniques and technologies for a given user interface problem
• build rapid prototypes of intelligent user interfaces
• evaluate intelligent user interfaces

General competence

On successful completion of this course the student can:

• analyse ethical aspects of automatic collection, storage, automatic interpretation and use of person-related measurements
• analyse opportunities and limitations associated with artificial intelligence and machine learning for given problems. 

The following required coursework must be approved before the student can take the exam:

Two individual oral presentations of a research article (45 minutes with questions). One presentation is on an assigned article and the second article is selected by the student.

Participation: There is a minimum 80% mandatory attendance in this course. Students who do not meet this requirement will not be allowed to sit the exam.