IKT440 ICT Seminar 1 (Autumn 2020)
- ECTS Credits:
- 7.5
- Responsible department:
- Faculty of Engineering and Science
- Course Leader:
- Lei Jiao
- Lecture Semester:
- Autumn
- Teaching language:
- English
- Duration:
- ½ year
Table of contents
The course is connected to the following study programs
- Cyber Security, Master’s Programme
- Artificial Intelligence and The Internet of Things, Master's Programme
- Artificial Intelligence, 5-year master programme
Teaching language
Learning outcomes
- be able to design, analyze, and implement basic systems, or solve basic problems selected from a range of ongoing research topics in ICT (or a project defined by an external company).
- The students should also have comprehensive knowledge of and the ability to work out functional solutions within their chosen fields of study.
Contents
The course is based on ongoing research in the department or in relevant industry. The course will deepen the expertise of a student within a focused application or research area. Individually or in small groups, students specialize in topics that are approved by members of the academic staff. The topics should be relevant for the specialization profile that the students have chosen. The students may be required to present scientific papers.
Pre-approved course topics:
- Artificial intelligence and learning systems (including one lecture introducing its application in eHealth). This topic is a compulsory basis for all students who want to proceed with the eHealth direction in ICT Seminar 2 (IKT441-G) and ICT Seminar 3 (IKT442-G) or 4 (IKT446-G).
- Cisco Certification Associate CCNA
- Embedded Systems
- 5G and IoT: Fundamentals
Be aware that not all topics in the seminar courses might be available every semester.
In addition to the pre-approved course topics, it is possible to propose a certain topic that a student can work on from research groups at UiA or from industry. The course responsible person must approve the topic based on two requirements: (1) The topic should be within the ICT domain and the technical depth of the topic is at Master level. (2) There is an employee at UiA with at least a Master's degree in the relevant field who is the supervisor of the topic.
Teaching and learning methods
The course is organized in combination of lectures, assignments, paper studies, labs, report writing and self-study. The tasks are done individually or in small groups with group supervision.
The workload for the average student is approximately 200 hours.