ACIT4720 Medical sensors and actuators Course description

No formal requirements over and above the admission requirements.

The student should have the following outcomes upon completing the course:

Knowledge

Upon successful completion of the course, the student:

• has a deep understanding of how data mining can be used to extract knowledge from data sets.
• has advanced knowledge of the different data mining algorithms

Skills

Upon successful completion of the course, the student:

• can design and implement data mining algorithms
• can deploy different data mining systems and configure them
• can utilize a specialized library for data mining

General competence

Upon successful completion of the course, the student:

• can use data mining systems to mine data
• can analyse data mining solutions with regard to robustness and in relation to his/her intended tasks
• can explain how data mining can be used in different applications areas such as business analytics

This course is divided into two parts. The first part with focus on covering the principles of data mining and stream processing. Different seminars will be given on the different methodological aspects of data mining and stream processing as well as the programming paradigms and software tools that enable them.

The second part will focus on the students completing a programming project. The project can be chosen from a portfolio of available problems. The student will work in a group on the project and submit a final code-base with a report.

During this part, there may be lectures if needed, but most of the time will be spent on individual supervision of students in lab-sessions.

Practical training

Lab sessions.

None.

Group project (2-4 students);(15 000 - 17 500 words)

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 applying 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.

This course covers the state of the art of technology and methods in the research within human-computer interaction and available computer systems.

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 advanced knowledge of multimodal user interfaces
• has advanced knowledge of input and output technologies
• can analyse problems and issues in interactions related to context, such as accessibility in public spaces, mobility problems, and the user's affective state
• can use knowledge of interaction technology to address new problems in universal design of ICT

Skills

On successful completion of this course the student

• can independently use appropriate methods of user centred interaction design and evaluation; both heuristic and automatic, in an independent manner
• can analyse and critically deal with the results from relevant research literature, apply these to structure and formulate scientific arguments, and assess the suitability of published results on new problems and issues
• can carry out independent, limited research or development projects under supervision and in accordance with applicable ethical standards
• can present scientific work orally
• can debate and conduct scientific discussions

General competence

On successful completion of this course the student

• can apply knowledge and skills in interaction technology on new problems and issues for carrying out advanced facilitation tasks and projects
• can communicate scientific problems, analysis and conclusions in the field to both specialists and the general public
• can contribute to original thinking and innovation processes

Two internal examiners. External examiner is used periodically. 

• Two individual oral presentations of research articles (45 min per presentation including questions).
• Being opponent against two student presentations.