•   Data Analytics RDI2HM102-3013 16.01.2023-17.03.2023  5   (MAICTE, ...) +-
    Starting level and linkage with other courses
    No prerequisites.
    Contents
    - Process thinking driven Data analytics
    - Descriptive, Predictive and Prescriptive analytics
    - Structured, unstructured and semi-structured data
    - Advanced data analytics
    - Algorithms in data analyses, e.g. machine learning algorithms in predicting
    - Significance, relevance and other important statistical terms to verify the outcome
    - Several applications are used, depending on the subject including the following non-exclusive list: Microsoft, SAP and Qlik analytics families, SPSS
    - Overview introduction to analytical coding enablers such as R, Python, C, SQL
    - Overview to Social Media analytics and related tools such as Google analytics and SAP Predictive Analytics, etc.
    - Visualization and reporting tools
    Assessment criteria
    Assessment criteria - grade 1
    The student understands the data analytics process and can apply it, instructed by the teacher, to a business problem. The student understands the following concepts: descriptive, predictive and prescriptive analytics as well as the characteristics of advanced data and is able to solve simple business questions, guided by the teacher.

    The student is able to derive and visualize dashboards, scorecards and publish those using related digital tools. The students is able to apply one or some forecasting algorithms to a business problem, instructed by the teacher. The students is able to assess the reliability and relevance of business reports.
    Assessment criteria - grade 3
    The student understands the data analytics process and can apply it independently to a simple business problem. The student understands the following concepts: descriptive, predictive and prescriptive analytics as well as the characteristics of advanced data and is able to solve simple business questions independently.

    The students is able to derive and visualize dashboards, scorecards and publish them using related digital tools. The student is able to apply independently one or some forecasting algorithms to a business problem. The students is able to assess the reliability and relevance of business reports.
    Assessment criteria - grade 5
    The student understands the data analytics process and can apply it to a slightly complicated business problem. The student understands the following concepts: descriptive, predictive and prescriptive analytics as well as the characteristics of advanced data and is able to solve demanding business questions.

    The student is able to derive and visualize dashboards, scorecards and publish them using related digital tools. The student is able to apply independently several forecasting algorithms to different business problems. The student is able to assess the reliability and relevance of business reports.
    Campus

    Pasila Campus

    Teaching language

    English

    Timing

    16.01.2023 - 17.03.2023

    Enrollment

    02.01.2023 - 13.01.2023

    Groups
    • MAICTE
    • EVENING
    • MAEXPE
    • CONTACT
    • MADIGE
    • EXCH
    Teachers

    Juha Nurmonen, Aki Taanila

    Seats

    31 - 50

    Degree Programme

    BUTEM Degree Programme in Business Technologies, ATBUM Degree Programme in Aviation and Tourism Business, LEBUM Degree Programme in Leading Business Transformation

    Evaluation scale

    H-5