•   Basics of Artificial Intelligence (AI) ICB011AS2AE-3002 15.01.2024-15.03.2024  5   (BLENDED, ...) +-
    Learning objectives
    Upon completion of the course, the student is able to:
    * understand what is AI and how it can affect business
    * recognize opportunities of AI in different domains
    * is able to analyze and visualize data
    * knows the basic statistical methods used in data analysis
    * knows how to use software to perform data analysis
    * knows how to apply some basic methods used in AI
    * knows trends in AI
    * can recognize ethical challenges related to applying AI in business
    Starting level and linkage with other courses
    No pre requirements
    Contents
    * definition of AI and basic concepts related to it
    * business cases where AI is used
    * methods and software for data analysis and visualization
    * basics of statistical data analysis methods
    * application of AI methods in a project work
    * recent trends in AI
    * ethical issues in AI
    Assessment criteria
    Assessment criteria - grade 1
    The student:
    - Knows the basic concepts of artificial intelligence
    - Recognizes the importance of artificial intelligence in business
    - Knows the most common AI methods
    - Knows th basics of technical solutions
    - Knows the needs and challenges of artificial intelligence projects and continuous development
    - Recognizes AI trends and ethical challenges
    Assessment criteria - grade 3
    In addition to the above the student:
    - Understands how artificial intelligence affects business
    - Understands in general the possibilities and limitations of various artificial intelligence software, platforms and services
    - Understands how it is possible to improve practices in artificial intelligence projects and continuous development
    - Understands the implications and ethical challenges of AI trends
    Assessment criteria - grade 5
    In addition to the above the student:
    - Is able to assess the best methods for the practical applications of artificial intelligence
    - Is able to compare the capabilities and limitations of different AI software, platforms and services
    - Is able to contribute to the organization's artificial intelligence projects and continuous development
    - Is able to analyze the effects of artificial intelligence trends and ethical challenges from the perspectives of individual organizations and society
    Further information
    When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

    Teaching methods and instruction

    Two sessions per week, the one is a contact lesson in Pasila Campus and the other one is online session. Participation to the sessions is not mandatory, but highly recommended. Sessions are not recorded.

    Learning material and recommended literature

    The course have weekly themes and related material on Moodle.

    Campus

    Pasila Campus

    Exam dates and re-exam possibilities

    The course has assignments and quizzes, no exam.

    Teaching language

    English

    Timing

    15.01.2024 - 15.03.2024

    Learning assignments

    The course contains one big team work, smaller assignments and quizzes. The team work can be done individually but it effects to the grade (some points are reduced).

    Enrollment

    02.01.2024 - 12.01.2024

    Content scheduling

    The threshold assignment (quiz) must be done during the first week of the course in order to continue at the course. Other assignments have also recommended deadlines, if not followed, it might effect to the grade (some points reduced).

    Groups
    • BLENDED
    • EXCH
    • ITE3PAICB1
    • ITE2PADIG1
    • CONTACT
    Alternative learning methods

    Prior learning can be recognized.
    Please contact the teacher latest during the first week of the course.

    Teachers

    Anne Wuokko, Jukka Remes

    Seats

    15 - 40

    Further information

    Assignments 65% (incl. team work 35%)
    Quizzes 35%
    (might come minor changes)

    Degree Programme

    ITBBA Business Information Technology

    R&D proportion

    0.00 cr

    Virtual proportion

    2.00 cr

    Evaluation scale

    H-5