CS-E4800 - Artificial Intelligence D, Lecture, 13.1.2022-7.4.2022

Inträde för gästanvändare
Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

The goal of Artificial intelligence (AI) is the creation of more intelligent computer programs, to be used as is, or as parts of intelligent autonomous systems, or in automating society's increasingly complex infrastructure. An intelligent system must obtain data, understand it, reason about it, and make decisions based on it, and the complexity of this process requires tools that are quite different from conventional software technologies.

This course covers some of the core areas of AI that are needed in creating intelligent systems, including automated reasoning, automated decision-making, problem solving, and game playing.

After completing the course, you will be capable of choosing the right technologies for solving many types of hard problems requiring intelligence, have an understanding of how to implement them, and understand better the basis of AI and its relation to other information technologies.

Credits: 5

Schedule: 13.01.2022 - 07.04.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Jussi Rintanen

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    State-space search algorithms. Automated reasoning in the propositional logic and the predicate logic. Applications in knowledge representation and natural language processing. Probabilistic reasoning. Decision-making under uncertainty. Adaptation and learning in decision-making. Adversarial decision-making in games and game theory.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Compulsory programming assignments,  tutorial exercises, and exam. The overall course grade depends on the  points earned from these sources.

Workload

  • valid for whole curriculum period:

    Lectures, exercise sessions,  independent work, and examination.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring III - IV
    2023-2024 Spring III - IV

    Enrollment :

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

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Aalto University Code of Academic Integrity and Handling Violations Thereof