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Neural Network Project (5 cr)

Code: TX00EY34-3003

General information


Enrollment
05.05.2025 - 19.10.2025
Registration for implementation has not started yet.
Timing
20.10.2025 - 14.12.2025
The implementation has not yet started.
Number of ECTS credits allocated
5 cr
Mode of delivery
On-campus
Unit
School of ICT and Industrial Management
Campus
Myllypurontie 1
Teaching languages
Finnish
Seats
0 - 35
Degree programmes
Information and Communication Technology
Teachers
Mikko Pere
Groups
TVT23-O
Ohjelmistotuotanto
Course
TX00EY34
No reservations found for implementation TX00EY34-3003!

Objective

The students applies neural networks to solve real-world problems. This includes analysing the problem domain, acquiring and exploring data, searching, experimenting and evaluating alternative solutions, implementing and validating the chosen solution, building data processing pipelines and deploying the solution.

Content

• Group work project in accordance with the objectives of the course
• Applying the machine learning process model from idea to product
• Problem-based use of neural network and machine learning libraries

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student's contribution to the project meets the objectives set.

Assessment criteria, good (3)

The student is an active member of the team, has a clear role in the project and performs it to achieve the project's objectives.

Assessment criteria, excellent (5)

The student plays a central and innovative role in the project and performs their task in an exemplary manner.

Assessment criteria, approved/failed

The student's contribution to the project meets the objectives set.

Qualifications

Data Handling and Machine Learning, Neutral Networks

Objective

The students applies neural networks to solve real-world problems. This includes analysing the problem domain, acquiring and exploring data, searching, experimenting and evaluating alternative solutions, implementing and validating the chosen solution, building data processing pipelines and deploying the solution.

Content

• Group work project in accordance with the objectives of the course
• Applying the machine learning process model from idea to product
• Problem-based use of neural network and machine learning libraries

Qualifications

Data Handling and Machine Learning, Neutral Networks

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