EPN-V2

PHVIT9200 Kvalitative metoder Emneplan

Engelsk emnenavn
Qualitative Methods
Studieprogram
Forskerlinje i helsevitenskap
Ph.d.-program i helsevitenskap
Doktorgradsstudium i helsevitenskap - enkeltemneopptak
Omfang
5.0 stp.
Studieår
2019/2020
Pensum
HØST 2019
Timeplan
Programplan
Emnehistorikk

Innledning

Grade scale A-F.

Forkunnskapskrav

Two internal examiners. External examiner is used periodically.

Læringsutbytte

Associate Professor Raju Shrestha

Arbeids- og undervisningsformer

  • Bachelor level knowledge in linear algebra, vector calculus, and basic statistics, and probability is important for understanding some of the concepts in this course.
  • Knowledge and skills in programming, particularly Python, and machine learning frameworks such as scikit-learn, TensorFlow, and Keras.

Arbeidskrav og obligatoriske aktiviteter

This course covers the fundamental principles of machine learning and deep learning methods and best practices in solving problems effectively. Most of the problems are related and applicable in many areas such as computer vision, surveillance, assistive technology, medical imaging, etc. Therefore, the course intends to provide case studies and examples of ML and DL in solving various problems. Students can explore the tremendous potential of modern AI, ML, and DL methods and techniques in solving problems in different application domains through project work.

Vurdering og eksamen

Individual home examination based on specific questions. To be submitted no more than 2 weeks after the end of the course. Answer papers must consist of up to 3,500 words.

Hjelpemidler ved eksamen

All

Vurderingsuttrykk

Pass / Fail

Sensorordning

One internal and one external examiner will assess the answer papers submitted by all candidates.

Opptakskrav

The course can also be offered to students who have been admitted to the “Health Science Research Programme, 60 ECTS”, by prior approval from the supervisor and based on given guidelines for the research programme.