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CS-E4800 - Artificial Intelligence, 10.01.2019-08.04.2019

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Syllabus

General

  • General

    General

    LecturersTomi Janhunen and  Jussi Rintanen
    TA


     Workload  Lectures 20h, exercise sessions 20h,  independent work 90h, examination 3h
    Learning Outcomes 

    Artificial intelligence (AI) is about making computers automating complex tasks that have earlier been only possible for intelligent human beings, including thinking and reasoning, problem solving, learning, and decision making. The goal of this course is to give an in-depth introduction to AI methodology. Having completed the course, you have gained a comprehensive overview of AI and understand its fundamental principles. You have acquired skills needed for solving real-world problems through intelligent software technologies.

     
    Content 

    The course presents a range of central AI techniques and  provides the students with an extensive toolbox for solving problems  in practice. Core AI techniques that show up in a broad range of applications include combinatory search methods, automated reasoning with logic and constraints, automated decision-making and planning, reinforcement learning, and supervised learning.


    Tentative Schedule
    Jan 10  1. Introduction to AI, Course organization
    Jan 17  2. Search methods (see the points of interest point of interest for the material presented at the lecture)
    Jan 24  3. Logical reasoning (with points of interest as above)
    Jan 31  4. Probabilistic reasoning (with points of interest as above)
    Feb  7  5. Decision making under uncertainty and imperfect information
    Feb 14  6. Applications via logic programming (with points of interest as above)
    Feb 28 7. Multi-agent decision making and games
    Mar  7  8. Supervised learning, Reinforcement learning
    Mar 14  9. Data mining (with points of interest as above)
    Mar 21 10. Applications and Summary

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    • School of Electrical Engineering (ELEC)
    • School of Engineering (ENG)
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