Deep learning (5cr)
Code: RO00FQ49-3002
General information
- Enrollment
- 02.12.2025 - 31.12.2025
- Registration for introductions has not started yet.
- Timing
- 01.01.2026 - 30.04.2026
- The implementation has not yet started.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- Department of Robotics, Construction and Energy Engineering
- Campus
- Kouvola Campus
- Teaching languages
- Finnish
- Course
- RO00FQ49
Unfortunately, no reservations were found for the realization Deep learning RO00FQ49-3002. It's possible that the reservations have not yet been published or that the realization is intended to be completed independently.
Objective
You can implement deep learning models through programming.
You know how to use libraries designed for deep learning.
You understand the significance of the cost function and gradients in optimization.
You can communicate using terminology related to neural networks.
You understand the purpose of activation functions.
You know how to modify your learning algorithm or data to improve model performance.
Content
What libraries are used for programming deep learning models?
How are deep learning models programmed?
How can the performance of a learning algorithm be improved?
What concepts are related to deep learning?
What are the application areas of deep learning?
Evaluation
a. use professional vocabulary and concepts in an expert way in different situations.
b. assess information sources critically.
c. work as team members in working life expert duties and identify and describe the problems of the professional field.
e. choose appropriate models, methods, software and techniques according to the purpose and justify these choices.
g. apply critically the ethical principles of the professional field in different situations.
Evaluation scale
1-5
Qualifications
Knowledge of applied mathematics, data analysis, and machine learning is required.