Deep learning 1 (5 cr)
Code: TT00CC66-3002
General information
- Enrollment
-
01.12.2023 - 31.01.2024
Registration for the implementation has ended.
- Timing
-
01.01.2024 - 16.04.2024
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- Teknologia
- Teaching languages
- Finnish
- Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Realization has 1 reservations. Total duration of reservations is 2 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Tue 16.04.2024 time 17:00 - 19:00 (2 h 0 min) |
Syväoppiminen 1 TT00CC66-3002 |
Teams opetus
|
Objective
The student understands the basics of deep learning and neural networks and the limitations and opportunities related to teaching them. The student can apply the methods used in deep learning in the Pytorch environment.
Content
- Artificial neurons and neural networks
- Deep learning with neural networks
- Teaching neural networks
- Use of trained neural networks
- Hyperparameters of neural networks
- Using the Pytorch environment
- CNN neural networks (Convolutional Neural Networks)
- RNN neural networks (Recurrent Neural Networks)
- Basics of natural language processing (NLP).
Evaluation scale
0 - 5
Prerequisites
Data science mathematics 1 (basic concepts of statistics)
Data science mathematics 2 (matrix algebra)
Python programming