•   Artificial Intelligence, Machine Learning, Human - Machine Interaction AMO18AI01-3005 10.02.2022-30.04.2022  5 credits  (AMO21HP-Å) +-
    Competence objectives of the study unit
    The Student

    - has an basic understanding of AI and the history of AI.
    - has knowledge of where AI is used and its development today.
    - has an basic understanding of different machine learning algorithms and their future possibilities
    - can recognize different inputs used in AI and machine learning
    - recognises the possibilities to get information and data from different systems and how Human - Machine Interaction is adapted in autonomous vessels
    Prerequisites
    No prerequisites.
    Content of the study unit
    - Administrative matters
    - Computational thinking and algoritms - What is computing? Algorithms and complexity
    - Introduction to AI and Autonomy - What is AI? How do you define Autonomy?
    - Agents and Search - How to solve problems with “Good old-fashioned AI”
    - Introduction to Machine Learning - Overview of ML, Risks and Problems with ML
    - Supervised learning - Basic supervised learning through regression
    - Machine vision - Deep neural networks, Image segmentation, Image detection, Image recognition
    - Reinforcement learning - Reinforcement learning as search, Autonomy and reinforcement learning
    - Industrial Internet - What is IoT? What is a Digital Twin?
    - Sensors and Sensor fusion - Situational awareness, LIDAR, IR, GNSS and IMU’s
    - Autonomy and Safety - Software safety, Liability, Accountability
    Assessment criteria
    Assessment criteria – satisfactory (1-2)
    Sufficient 1
    Theory and methodology are poorly understood and implemented in Autonomous Maritime Operation related tasks/ assignments.
    Research, communication and documentation are hardly acceptable.
    Active participation.
    Satisfactory 2
    Appear to grasp theory and have made a start in showing its applicability in Autonomous Maritime Operation related tasks/ assignments. Research, communication and documentation are acceptable.
    Active participation.
    Assessment criteria – good (3-4)
    Good 3
    Understanding of theory and applicability of methods in Autonomous Maritime Operation related tasks/ assignments, but work could be stronger.
    Research, service design, communication and documentation are good.
    Active participation.
    Very Good 4
    General understanding of theory and methods, very good implementation in Autonomous Maritime Operation related tasks/ assignments.
    Reliable research, innovative service design and communication and documentation on good level.
    Very active participation.
    Assessment criteria – excellent (5)
    Excellent 5
    Mastery of theory and methods, proficiency of implementation of them in Autonomous Maritime Operation related tasks/ assignments.
    Outstanding research, innovative service design and excellent communication and documentation.
    Very active participation.
    Name of lecturer(s)

    Thomas Finne

    Teaching language

    English

    Timing

    10.02.2022 - 30.04.2022

    Enrollment date range

    15.11.2021 - 31.03.2022

    Group(s)
    • AMO21HP-Å
    Responsible unit

    Faculty of Technology and Seafaring

    Teachers and responsibilities

    Johan Westö

    Degree Programme(s)

    Degree Programme in Autonomous Maritime Operations

    Campus

    Åbo, Hertig Johans parkgata 21

    Assessment scale

    H-5