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Introduction to Machine Learning

  • Credits 2  credits
  • Education ordinance First cycle
  • Study location Distance with no obligatory meetings
  • Course code DVA133
  • Main area Computer Science

Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML). The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.

In this course you learn the foundation of Machine Learing.

About the course

Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML).

The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.


Entry requirements

Mathematics C or Mathematics 3b/3c.

You can also apply for the course and get your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies etc. Read more in Application information below.

Language

English

Occasions for this course

Spring semester 2021

  • Spring semester 2021

    Scope

    2 credits

    Time

    2021-01-18 - 2021-06-06 (part time 10%)

    Education ordinance

    First cycle

    Course type

    Independent course

    Application code

    MDH-14131

    Language

    English

    Study location

    Independent of location

    Teaching form

    Distance learning
    Number of mandatory occasions including examination: 0
    Number of other physical occasions: 0

    Course syllabus & literature

    See course plan and literature list (DVA133)

    Requirements

    Mathematics C or Mathematics 3b/3c

    Selection

    Upper secondary (high school) grades, Swedish Scholastic Aptitude Test, University credits

  • Autumn semester 2021

    Scope

    2 credits

    Time

    2021-08-30 - 2022-01-16 (part time 10%)

    Education ordinance

    First cycle

    Course type

    Independent course

    Application code

    MDH-24037

    Language

    English

    Study location

    Independent of location

    Teaching form

    Distance learning
    Number of mandatory occasions including examination: 0
    Number of other physical occasions: 0

    Course syllabus & literature

    See course plan and literature list (DVA133)

    Requirements

    Mathematics C or Mathematics 3b/3c

    Selection

    Upper secondary (high school) grades, Swedish Scholastic Aptitude Test, University credits

  • Spring semester 2022

    Scope

    2 credits

    Time

    2022-01-17 - 2022-06-05 (part time 10%)

    Education ordinance

    First cycle

    Course type

    Independent course

    Application code

    MDH-14131

    Language

    English

    Study location

    Independent of location

    Teaching form

    Distance learning
    Number of mandatory occasions including examination: 0
    Number of other physical occasions: 0

    Course syllabus & literature

    See course plan and literature list (DVA133)

    Requirements

    Mathematics C or Mathematics 3b/3c

    Selection

    Upper secondary (high school) grades, Swedish Scholastic Aptitude Test, University credits

Questions about the course?

If you have any questions about the course, please contact the Course Coordinator.

Professor

Shahina Begum

+4621107370

shahina.begum@mdh.se

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