Applied Machine Learning


Content, progress and pedagogy of the module

The course gives a comprehensive introduction to machine learning and its application in manufacturing engineering. The field is concerned with learning from data and has roots in computer science, statistics and pattern recognition. The objective is realized by presenting methods and tools proven valuable and by addressing specific application problems.

Learning objectives


  • Must have knowledge about the steps of a machine learning project pipeline.
  • Must have knowledge about supervised and unsupervised learning methods.
  • Must have knowledge about machine learning fundamentals, software, frameworks, tools, and public datasets.


  • Must be able to apply the taught methods to solve concrete engineering problems.
  • Must be able to evaluate and compare the methods within a specific application problem.
  • Must be able to build a machine learning project pipeline.
  • Must be able to understand the value of a machine learning solution in a business context.


  • Must have competencies in analyzing a given problem and identifying appropriate machine learning methods to the problem.
  • Must have competencies in understanding the strengths and weaknesses of the methods.
  • Must have competencies in evaluating a machine learning solution’s advantages and limitations.

Type of instruction

The criteria of assessment are stated in the Examination Policies and Procedures, § 17.



Name of examApplied Machine Learning
Type of exam
Written or oral exam
Permitted aidsInformation about allowed helping aids for the examination will be published in the description of the semester/module.
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleAnvendt maskinlæring
Module codeM-MT-K1-5
Module typeCourse
Duration1 semester
Language of instructionEnglish
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Education ownerMaster of Science (MSc) in Engineering (Mechanical Engineering)
Study BoardStudy Board of Mechanical Engineering and Physics
DepartmentDepartment of Materials and Production
FacultyThe Faculty of Engineering and Science