CS-E4650 - Methods of Data Mining D, Lecture, 5.9.2022-14.12.2022

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

After the course, the students have an overview of the main principles and methods of data mining and know how to apply them on real world problems. They know the most fundamental pattern types and their search methods, including associative and graph mining, main approaches to cluster large-dimensional and heterogenous data, basic
concepts and techniques in social network analysis, web and text mining, and how to validate the data mining results.

Credits: 5

Schedule: 05.09.2022 - 14.12.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Jorma Laaksonen

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:

    The course covers fundamental data mining problems, such as pattern discovery, graph mining, and clustering different types of data. The main emphasis is in learning the basic principles of data mining and their application in practice, including method selection, validation, and scalablity issues.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Home assignments, project work, examination.

Workload

  • valid for whole curriculum period:

    Study methods consist of lectures (24h), exercise sessions (8h), home assignments and project work (about 76h), self-studying (24h), and exam. Lectures and exercise sessions are voluntary and can be replaced by self studying.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Autumn I - II
    2023-2024 Autumn I - II

    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