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Project studies 2 - Machine learningLaajuus (5 cr)

Code: TT00CC64

Credits

5 op

Teaching language

  • Finnish

Objective

In the course, students learn to apply machine learning methods in real practical tasks. As part of the course, students work in small groups to develop an application that uses machine learning. During the project, students prepare a comprehensive project plan, analyze and understand the given data, perform data pre-processing and storage, and apply suitable machine learning models to analyze the dataset and report the results of their project.

en
Enrollment

02.07.2025 - 31.07.2025

Timing

01.08.2025 - 31.12.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Degree programmes
  • Bachelor’s Degree in Information and Communication Technology
Teachers
  • Mikko Romppainen
  • Jani Sourander
Groups
  • TTM24SAI
    TTM24SAI

Objective

In the course, students learn to apply machine learning methods in real practical tasks. As part of the course, students work in small groups to develop an application that uses machine learning. During the project, students prepare a comprehensive project plan, analyze and understand the given data, perform data pre-processing and storage, and apply suitable machine learning models to analyze the dataset and report the results of their project.

Evaluation scale

0 - 5

en
Enrollment

19.08.2024 - 22.09.2024

Timing

01.08.2024 - 31.12.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Degree programmes
  • Bachelor’s Degree in Information and Communication Technology
Teachers
  • Mikko Romppainen
  • Jani Sourander
Groups
  • TTM23SAI
    TTM23SAI

Objective

In the course, students learn to apply machine learning methods in real practical tasks. As part of the course, students work in small groups to develop an application that uses machine learning. During the project, students prepare a comprehensive project plan, analyze and understand the given data, perform data pre-processing and storage, and apply suitable machine learning models to analyze the dataset and report the results of their project.

Evaluation scale

0 - 5

en
Enrollment

01.08.2023 - 29.10.2023

Timing

30.10.2023 - 31.12.2023

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Degree programmes
  • Bachelor’s Degree in Information and Communication Technology
Teachers
  • Jussi Ala-Hiiro
Groups
  • TTM22SAI
    TTM22SAI

Objective

In the course, students learn to apply machine learning methods in real practical tasks. As part of the course, students work in small groups to develop an application that uses machine learning. During the project, students prepare a comprehensive project plan, analyze and understand the given data, perform data pre-processing and storage, and apply suitable machine learning models to analyze the dataset and report the results of their project.

Evaluation scale

0 - 5

en
Enrollment

01.08.2023 - 29.10.2023

Timing

30.10.2023 - 31.12.2023

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Degree programmes
  • Bachelor’s Degree in Information and Communication Technology
Teachers
  • Mikko Romppainen
  • Jussi Ala-Hiiro
Groups
  • TTV22SAI
    TTV22SAI

Objective

In the course, students learn to apply machine learning methods in real practical tasks. As part of the course, students work in small groups to develop an application that uses machine learning. During the project, students prepare a comprehensive project plan, analyze and understand the given data, perform data pre-processing and storage, and apply suitable machine learning models to analyze the dataset and report the results of their project.

Evaluation scale

0 - 5