CS-E4875 - Research Project in Machine Learning, Data Science and Artificial Intelligence D, Lecture, 22.9.2021-25.5.2022

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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 student knows how to carry out a scientific project and write a scientific report in the field of machine learning, data science and artificial intelligence.

Credits: 10

Schedule: 22.09.2021 - 25.05.2022

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):

jorma.laaksonen@aalto.fi

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:

    A project work, done either alone or in a group, from the field of machine learning, data science and artificial intelligence.  Students can either 1) report the research work carried out during their internships, 2) find a topic and supervisor by themselves, or 3) select a topic among available ones in a matchmaking process run in September.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Assesment based on the report and presentation.

  • applies in this implementation

    The supervisor assesses the project report.  The presentation is optional.

Workload

  • valid for whole curriculum period:

    Independent or group work including discussions with a supervisor, programming, experimenting, reporting and presenting the results.

  • applies in this implementation

    1 ECTS credit point matches 27 hours of work.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

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

    Enrollment :

    The course is primarily available for major students in CCIS Machine Learning, Data Science and Artificial Intelligence (Macadamia) and exit year students in EIT Digital Master School's Data Science major. Other students need to contact the responsible teacher before enrolling.

Details on the schedule

  • applies in this implementation

    The only meeting is on Wednesday 22.9.2021 14:15-15:00 in https://aalto.zoom.us/j/6980731607 .

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof