Neural Network Project (5 ECTS)

Learning outcomes

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

Prerequisites

Data Handling and Machine Learning, Neutral Networks

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.