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  • Högskolepoäng 2.5  hp
  • Utbildningsnivå Avancerad nivå
  • Studieort Distans utan obligatoriska träffar
  • Kurskod DVA478
  • Huvudområde Datavetenskap

The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling

About this course

The course aims to give insights in fundamental concepts of machine learning for predictive analytics to provide actionable, i.e., better and more informed decisions in, forecasting. It covers the key concepts to extract useful information and knowledge from data sets to construct predictive modeling.

Introduction: overview of Predictive data analytics and Machine learning for predictive analytics.

Data exploration and visualization: presents case studies from industrial application domains and discusses key technical issues related to how we can gain insights enabling to see trends and patterns in industrial data.

Predictive modeling: consists of issues in construction of predictive modeling, i.e., model data and determine Machine learning algorithms for predicative analytics and techniques for model evaluation.

You will learn

  • Select suitable machine learning algorithms to solve a given problem for predictive data analytics.
  • Explore data and produce datasets suitable for analytical modeling.
  • Basics of machine learning for predictive analytics

Entry requirements

  • 90 credits of which at least 60 credits in Computer Science or equivalent, including 15 credits in programming as well as 2,5 credits in basic probability theory and 2,5 credits in linear algebra, or equivalent.
  • In addition English course A/English course 6 is required.

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.

Language

English

Tillfällen för denna kurs

Hösttermin 2021

  • Hösttermin 2021

    Omfattning

    2.5 hp

    Tid

    2021-11-29 - 2022-01-16 (deltid 25%)

    Utbildningsnivå

    Avancerad nivå

    Kurstyp

    Fristående kurs

    Anmälningskod

    MDH-24546

    Språk

    Engelska

    Studieort

    Ortsoberoende

    Undervisningsform

    Distans
    Antal obligatoriska träffar inklusive tentamen: 0
    Antal övriga fysiska träffar: 0

    Särskild behörighet

    90 hp, varav 60 hp inom datavetenskap eller motsvarande, inklusive 15 hp programmering samt 2,5 hp grundläggande sannolikhetsteori och 2,5 hp linjär algebra, eller liknande. Dessutom krävs Svenska B/Svenska 3 samt Engelska A/Engelska 6. I de fall kursen ges på engelska görs undantag från kravet på Svenska B/Svenska 3.

    Urval

    Antal högskolepoäng

Frågor kring utbildningen?

Hör av dig till kursansvarig om du har frågor kring kursens innehåll.

Professor i artificiell intelligens

Shahina Begum

021-10 73 70

shahina.begum@mdh.se

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