•   Data Analytics 5N00EI59-3003 23.08.2021-24.12.2021  3 cr  (20TIETOA) +-
    Learning outcomes of the course unit
    The student
    - is able to handle data sets
    - has basic knowledge of mathematics related to data-analysis
    - is able to use and apply classical data analysis for solving technical problems
    - is familiar with basics and methods of regression, classification and clustering
    Course contents
    • Classical Data Analysis
    • Classification, Decision Trees, Random Forests
    • Clustering, K-means
    • Regression, Linear Regression, Logistic Regression
    • Basics of Neural Network
    Assessment criteria
    Satisfactory

    The student is able to handle data and knows the basics of data analysis and the related key methods. The student is able to calculate simple tasks related to the topics of the course, which are similar to the examples presented.

    Good

    In addition to the above, the student is able to apply the course knowledge in new situations and justify his/her solutions. The student is able to use the concepts and methods related to the subjects of the course correctly. The student performs the given tasks independently.

    Excellent

    In addition to the above, the student has a comprehensive understanding of the course topics and their use in problem solving, as well as the ability to present and justify his/her solutions logically.

    Name of lecturer(s)

    Miika Huikkola

    Recommended or required reading

    Moodlessa ilmoitettu ja julkaistava materiaali (not translated)

    Planned learning activities and teaching methods

    Lähiopetus / etäopetus, yhteisöllinen oppiminen, harjoitustehtävät, harjoitustyöt (not translated)

    Assessment methods and criteria

    Opintojakson suorittaminen perustuu seuraaviin osa-alueisiin
    Aktiivinen osallistuminen opetukseen
    Harjoitustyö(t)
    Harjoitustehtävät
    Loppukoe / tentti (not translated)

    Language of instruction

    Finnish

    Timing

    23.08.2021 - 24.12.2021

    Registration

    01.06.2021 - 03.09.2021

    Credits

    3 cr

    Group(s)

    20TIETOA

    Seats

    0 - 50

    Teacher(s)

    Miika Huikkola

    Degree programme(s)

    Degree Programme in ICT Engineering, students who began in 2014-2018

    Office

    TAMK Main Campus

    Evaluation scale

    0-5

    Exam schedule

    Loppukoe viimeisellä opetusviikolla Moodlessa ilmoitettavana ajankohtana

    Uusintatentit
    dd.1.2022 klo 17-20
    dd.2.2022 klo 17-20 (not translated)

    Students use of time and load

    Oppitunteja n. 30 h
    Itsenäinen opiskelu n. 25 h
    Harjoitustyö n. 25 h (not translated)

    Content periodicity

    -Matlab perusteet
    -Klassinen data-analyysi
    -Data-analyysin menetelmiä
    -Harjoitustyöt (not translated)