•   Intelligent process automation 5W00FK35-3001 30.08.2021-27.11.2021  5 cr  (21YAR) +-
    Learning outcomes of the course unit
    A student understands a definition of intelligent process automation with a set of different functionalities. A student recognises applications of intelligent process automation and understands its applicability, limitations and achievable benefits. A student can engineer some of the functionalities of intelligent process automations.
    Course contents
    Intelligent process automation with
    - its description and definition
    - methods and functionalities
    - principles, limitations and achievable benefits
    - applications and use cases
    Assessment criteria
    Satisfactory

    A student understands a definition of intelligent process automation. A student recognises some functionalities of intelligent process automation. A student recognises an application of intelligent process automation.

    Good

    In addition to the criteria listed above, a student understands several functionalities of intelligent process automation with limitations and achievable benefits. A student recognises applications of intelligent process automation.

    Excellent

    In addition to the criteria listed above, a student widely understands and recognises functionalities, limitations and achievable benefits of intelligent process automation. A student recognises several applications of intelligent process automation and can engineer applications of intelligent process automations.


    Name of lecturer(s)

    Anne Cumini

    Recommended or required reading

    Lectures, notes made by a student, other referred material by a lecturer

    Planned learning activities and teaching methods

    Virtual teaching, home excercises (individual and/or working group), self-learning.

    Assessment methods and criteria

    Student performance assessment is based on the given and qualified exercises.

    Language of instruction

    Finnish

    Timing

    30.08.2021 - 27.11.2021

    Registration

    02.07.2021 - 18.09.2021

    Credits

    5 cr

    Group(s)

    21YAR

    Teacher(s)

    Pasi Airikka

    Further information for students

    Enthusiasm on the course content and learning is recommended.

    Unit, in charge

    MD in Automation in Smart Industry

    Degree programme(s)

    Master's Degree Programme in Automation in Smart Industry

    Office

    TAMK Main Campus

    Evaluation scale

    0-5

    Completion alternatives

    None.

    Training and labour cooperation

    None.

    Exam schedule

    There is no exam in the course. A failed course can be passed by completing all the exercises given in the course.

    International connections

    The course involves no travelling abroad.

    Students use of time and load

    The total estimated working hours for succesfully passing the course is ca. 133 hours (5 cr x 1600/60 h/cr) of which a student has to allocate a major part for self-learning.

    Content periodicity

    The more detailed course structure is introduced in the first class and it will be available in the course information on Moodle afterwards.