•   Data Analytics and Artificial Intelligence in Health Care 7Y00FJ97-3002 01.08.2022-31.12.2022  5 cr  (22YHS, ...) +-
    Learning outcomes of the course unit
    The student
    - knows the most common terminology and concepts of data analytics
    - knows the principles of data mining, storing and analysis mehtods
    - knows the most common data management and visualisation methods
    - understands the importance and use data in health care process
    - knows the concepts, principles and use of machine learning in health care
    Course contents
    Key concepts: definition of healthcare data, Big Data, data visualization, algorithms, machine learning, artificial intelligence
    Categories of health care data
    Introduction to Big Data and its utilization in healthcare
    Data recovery methods
    The most common Big Data systems
    Introduction to algorithms, basics of machine learning and artificial intelligence
    Assessment criteria
    Satisfactory

    The student

    - is able to process data

    - is able to analyze and make data visualizations

    - knows the basics and main concepts of artificial intelligence as well as the main applications in the field of healthcare.

    Good

    The student

    - is able to process data

    - is able to analyze and make data visualizations

    - knows the basics and main concepts of artificial intelligence

    - is able based on examples to create artificial intelligence applications in the field of healthcare

    - understands the importance of data in health care management processes.

    Excellent

    The student

    - is able to process data

    - is able to analyze and make data visualizations

    - knows well the basics of artificial intelligence and the most important concepts

    - is able to create appropriate artificial intelligence applications in healthcare

    - understands the importance of data in health care management processes.


    Name of lecturer(s)

    Tony Torp

    Language of instruction

    Finnish

    Timing

    01.08.2022 - 31.12.2022

    Registration

    02.07.2022 - 31.07.2022

    Credits

    5 cr

    Group(s)

    22YHS

    22YHT

    22YHL

    Teacher(s)

    Ossi Nykänen, Lea Saarni, Tony Torp

    Unit, in charge

    MD in Wellbeing Technology

    Degree programme(s)

    Master's Degree Programme in Well-Being Technology, Master's Degree Programme in Well-Being Technology, Master's Degree Programme in Well-Being Technology

    Office

    TAMK Main Campus

    R&D proportion

    1 cr

    Evaluation scale

    0-5