•   Applied Artificial Intelligence (AI) ICB013AS3AE-3005 20.10.2025-12.12.2025  5   (IT4PAICB1, ...) +-
    Learning objectives
    The overall learning objective of the course is to give the students insight into machine learning and natural language processing (NLP) technologies and their application in practice.
    Upon successful completion of the course, the student:
    • knows the main concepts of machine learning and natural language processing,
    • can apply a machine learning method in a business case,
    • can build a simple chatbot,
    • has gained basic skills in using selected machine learning and NLP tools and
    • is capable of planning and implementing a project involving AI technologies
    Contents
    • Main concepts of machine learning and natural language processing.
    • Business cases where machine learning and natural language processing methods are used.
    • Tools (e.g. Anaconda, Python library scikit-learn ) for machine learning.
    • Tools (e.g. Google Dialogflow, IBM Watson Virtual Assistant)
    • Course project involving AI technologies.
    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

    The course is virtual, requiring independent study and group work skills virtually. The learning environment is Moodle. Moodle contains learning materials and instructions.

    The implementation involves a group assignment. This requires online meetings of groups (3-5 people).

    Course materials are available at the start of the course. Current company lectures and other materials may be added during the course, but these will be announced separately.

    Learning material and recommended literature

    Coursebook is Machine Learning Engineering with Python (Second edition) from Andrew P. McMahon, Adi Polak.

    Course book is available in Haaga-Helia online library.

    Also there is material available in Moodle.

    Campus

    Pasila Campus

    Teaching language

    English

    Timing

    20.10.2025 - 12.12.2025

    Learning assignments

    The course contains some individual assignments and group assignment.

    Enrollment

    14.05.2025 - 22.05.2025

    Content scheduling

    Course is virtual and deadlines for the assignments can be found from the Moodle.

    Groups
    • IT4PAICB1
    • ITE4PADIG1
    • ITE4PAICB1
    • VIRTUAL
    • INSTRUCTED
    • ITB4PAICB1
    Teachers

    Jukka Remes, Ville Pennanen

    Seats

    30 - 60

    Degree Programme

    TRATI Tradenomi tietojenkäsittely

    R&D proportion

    0.00 cr

    Virtual proportion

    5.00 cr

    Evaluation scale

    H-5