Online learningLaajuus (5 cr)
Code: TT00CC71
Credits
5 op
Teaching language
- Finnish
Objective
The student knows how to create a neural network for online learning, as well as enable it on the server and publish it. The student can adjust the hyperparameters of the neural network so that the neural network learns more from user data. (E.g. recommender neural networks or congestion predicting neural networks.)
Assessment criteria, excellent (5)
A grade of 5 requires completing and returning all course exercises, as well as a commendable reflection on the exercises.
Assessment criteria, satisfactory (1)
For a grade of 1, it is required that the returned course exercises show that the student knows how to use a ready-made neural network in an online environment.
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
- Pekka Huttunen
- Jani Sourander
Groups
-
TTM23SAITTM23SAI
Objective
The student knows how to create a neural network for online learning, as well as enable it on the server and publish it. The student can adjust the hyperparameters of the neural network so that the neural network learns more from user data. (E.g. recommender neural networks or congestion predicting neural networks.)
Evaluation scale
0 - 5
Assessment criteria, excellent (5)
A grade of 5 requires completing and returning all course exercises, as well as a commendable reflection on the exercises.
Assessment criteria, satisfactory (1)
For a grade of 1, it is required that the returned course exercises show that the student knows how to use a ready-made neural network in an online environment.
Prerequisites
Deep learning 1
Deep learning 2
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
- Pekka Huttunen
- Jani Sourander
Groups
-
TTM22SAITTM22SAI
Objective
The student knows how to create a neural network for online learning, as well as enable it on the server and publish it. The student can adjust the hyperparameters of the neural network so that the neural network learns more from user data. (E.g. recommender neural networks or congestion predicting neural networks.)
Evaluation scale
0 - 5
Assessment criteria, excellent (5)
A grade of 5 requires completing and returning all course exercises, as well as a commendable reflection on the exercises.
Assessment criteria, satisfactory (1)
For a grade of 1, it is required that the returned course exercises show that the student knows how to use a ready-made neural network in an online environment.
Prerequisites
Deep learning 1
Deep learning 2
Enrollment
02.07.2024 - 31.07.2024
Timing
01.08.2024 - 27.10.2024
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
Objective
The student knows how to create a neural network for online learning, as well as enable it on the server and publish it. The student can adjust the hyperparameters of the neural network so that the neural network learns more from user data. (E.g. recommender neural networks or congestion predicting neural networks.)
Evaluation scale
0 - 5
Assessment criteria, excellent (5)
A grade of 5 requires completing and returning all course exercises, as well as a commendable reflection on the exercises.
Assessment criteria, satisfactory (1)
For a grade of 1, it is required that the returned course exercises show that the student knows how to use a ready-made neural network in an online environment.
Prerequisites
Deep learning 1
Deep learning 2
Enrollment
19.08.2024 - 22.09.2024
Timing
01.08.2024 - 27.10.2024
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
- Pekka Huttunen
- Jani Sourander
Groups
-
TTV22SAITTV22SAI
Objective
The student knows how to create a neural network for online learning, as well as enable it on the server and publish it. The student can adjust the hyperparameters of the neural network so that the neural network learns more from user data. (E.g. recommender neural networks or congestion predicting neural networks.)
Evaluation scale
0 - 5
Assessment criteria, excellent (5)
A grade of 5 requires completing and returning all course exercises, as well as a commendable reflection on the exercises.
Assessment criteria, satisfactory (1)
For a grade of 1, it is required that the returned course exercises show that the student knows how to use a ready-made neural network in an online environment.
Prerequisites
Deep learning 1
Deep learning 2