Machine Intelligence

2021/2022

Prerequisite/Recommended prerequisite for participation in the module

It is recommended that the student has knowledge of discrete mathematics, algorithms and data structures

Content, progress and pedagogy of the module

Disclaimer.
This is an English translation of the module. In case of discrepancy between the translation and the Danish version, the Danish version of the module is valid.

Learning objectives

Knowledge

The student should gain knowledge of the following theories and methods:

  • problem solving using search and inference
  • model-based decision making
  • inference under uncertainty
  • learning from experience and learning from data

Skills

  • use correct technical notation and terminology in writing as well as speech
     
  • apply basic techniques presented in the course to solve a specific problem
     
  • explain key principles and algorithms presented in the course

Competences

  • be able to evaluate, compare and select techniques and methods within machine intelligence based on a specific problem

Type of instruction

The type of instruction is organised in accordance with the general instruction methods of the programme, cf. § 17.

Extent and expected workload

The student is expected to spend 27.5 hours per ECTS, which for this activity means 137.5 hours.

Exam

Exams

Name of examMachine Intelligence
Type of exam
Written or oral exam
ECTS5
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Contact: The Study board for Computer Science at cs-sn@cs.aau.dk or 9940 8854

Facts about the module

Danish titleMaskinintelligens
Module codeDSNDATFB513
Module typeCourse
Duration1 semester
SemesterAutumn
ECTS5
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyTechnical Faculty of IT and Design