Topic outline

  • General

    Introduction to Artificial Intelligence

    • Lectures on Fridays at 14:15–16:00 (hall T1, starting March 3)
    • Exercise kick-off sessions on Tuesdays at 14:15 (hall B, starting March 7)
    Login to access lecture material and assignments. Lectures are in-person, but video recordings will be available afterwards. Thus, the course can be taken remotely but requires a commitment to work on a weekly basis. The course is targeted basically to anyone at Aalto with an interest in learning about artificial intelligence.

    Lecturer:
    Prof. Arno Solin

    TAs:
    Head-TA: Dr. Marcus Klasson (marcus.klasson@aalto.fi)
    Rui Li, Riccardo Mereu, Haishan Wang

    Contact information:

    For practical questions, please contact the head-TA. Include the course code "CS-C1000" in the message subject.

    Content:
    This course is intended as a primer in artificial intelligence (AI). The course goes through basic concepts (with examples) in AI, covering topics in symbolic AI, data mining, and machine learning. The overall goal is demystifying these concepts and give the students a basic understanding of the past, the present, and a bit about the future of AI. This course is intended as a non-technical introduction, which means that prior skills in programming or mathematics are not required.

    Outcomes:
    After the course, the student has an understanding of basic concepts in AI and ML. The student should understand the setup behind common AI systems, and know some of the possibilities and limitations they have.

    Assessment:
    Lecture quizzes, essays, and computer exercise demos. No physical presence is required.

    Workload:
    Lectures 12 h, exercise sessions 12 h, independent work 55 h. Students are awarded 3 cr for completing the course.

    Material:
    Lecture material, exercise notebooks, additional reading material.

    Prerequisites:
    Students from all study programs are welcome, and thus no formal requirements are set. Basic understanding of concepts in high-school mathematics and statistics. Students with no background in engineering are encouraged to glance through, e.g., the excellent material of Elements of AI (https://www.elementsofai.com/).

    Grading scale:
    0–5

    Language:
    English