Københavns Erhvervsakademi

en

IoT og dataanalyse (DA)

2018/2019
Engelsk titel
IoT and Data Analytics (DA)
Uddannelse
Økonomi & Informationsteknologi
Uddannelsestype
Fuldtidsuddannelse
Niveau
Professionsbachelor
Semester
5. semester
Fagets/modulets varighed
10 uger
Ects
15
Udd. element
Valgfag
Sprog
Dansk
Opstart
Efterår
Studiested
Lygten 16, København NV
Fagkode
9141553
Fag- /modulansvarlig
Leif Schwartz Holbek
Kim Juhl
Jesper Skovsgaard Frederiksen
Guillaume Nadon
  • Indhold og læringsmål

    Companies in all sizes are these years being pushed to
    make a Digital Transformation of their business – some
    sources even states, that companies failing to do it will
    simply cease to exist in the future.
    Internet of Things (IoT) is one of the new technologies
    that companies uses to make a digital transformation of
    and in some industries IoT will simple disrupt the current
    business models. In this elective you will get solid
    understanding of IoT and insight to what it can be used
    to. You will be introduced to different IoT Development
    Suites for both IoT devices and back-end systems. This
    will include programming on different levels, e.g. will
    Python be introduced, but higher level programming will
    be used as well.
    Data Analytics is another tool for companies in driving
    their Digital Transformation and have already been used
    for many years by many companies. IoT will drive this
    further and in this elective we will look into how to
    combine IoT and Data Analytics. Data Analytics in
    various forms will be in focus in this elective.

    Learning goals made simple – a summary
    The course will give the student deeper knowledge about both IoT and Data Analytics.
    The student will learn about different IoT development suites and systems, and be able to participate in or lead an IoT project in a future job position.
    The student will obtain knowledge about how IoT and Data Analytics can be combined for optimisation or creating new business models.

  • Undervisningsform
    A mix of theory and practice. There will be lectures followed by case exercises, which will involve cooperation with KEA’s external partners.
    A special emphasis will be put on hands-on experience with programming, IoT Development Suites and Data Analytics tools.
    We will work together with many external partners, have guest speakers and do some company visits to explore some of the current ongoing work in this field out there.
    The elective will be based on hands out and different literature.

    NOTE!
    During the elective there will be two mandatory group case hand-ins. Each of these includes a small report and a class presentation. The two cases will be evaluated and has to be approved before the group/student can take the final elective exam.
  • Forudsætninger for at deltage i faget

    Materielle forudsætninger for at deltage i faget
    Vi antager, at studerende har en bærbar computer, der kører Windows 10 (eller senere) eller Mac OS X 10.12 (eller senere).

    Ældre versioner af Windows eller Mac OS og Linux kan muligvis virke i de fleste tilfælde - men understøttes ikke med hjælp til at installere open source-værktøjer eller håndtere undervisningseksempler.

    Vi antager, at eleverne har en HDMI-port eller miniDVI / lynport på deres bærbare computer.
    I nogle få læringssituationer (ikke i 1. semester) bruges eksempler, der ikke så godt virker med mindre end 4 GB RAM-hukommelse - for dette 8 GB RAM anbefales.

    Studerende vil have brug for kontorsoftware (Microsoft, Apple, Google eller ..).
    Studerende skal kunne producere og læse pdf-dokumenter, Word-dokumenter, PowerPoint-præsentationer og Excel-regneark.

    Der findes en Microsoft Cloud-version, der bliver tilgængelig, når du opretter en gratis endrevskonto.

    En internetbrowser skal være tilgængelig (dvs. Chrome eller Safari).
    Vi anbefaler stærkt eleverne at have adgang til Facebook og en privat Facebook-konto.

  • Prøve

    Læringsmålene for prøven er identiske med fagets/fagenes læringsmål

    Faget prøves
    Faget/modulet prøves selvstændigt
    Prøveform
    Skriftlig prøve
    Individuel eller gruppeprøve
    Gruppeprøve, 2-4 maks. deltagere
    Anvendt sprog til prøven
    Engelsk
    Bedømmelsesform
    7-trins skala
    Bedømmer(e)
    Intern censur
77
timer undervisning
334
timer forberedelse
Tallene viser omfanget af arbejdsbelastningen relateret til faget fordelt på forskellige studieaktiviteter.

På faget IoT og dataanalyse (DA) modtager du 77 timers undervisning, hvilket svarer til 102 lektioner (1 lektion = 45 min.) og 19% af din samlede arbejdsbelastning på faget.

Undervisningen vil primært bestå af følgende aktiviteter: klasseundervisning.
Forberedelsen vil primært bestå af følgende aktiviteter: projektarbejde.

Læs om KEAs studieaktivitetsmodel

*KEA kan fravige det angivne timetal, hvis det er begrundet i særlige forhold.