Master’s Degree Programme in Engineering, from IoT to AI (in Finnish)
Master of Engineering, from IoT to AI (in Finnish) 23S, online studies
Master of Engineering, from IoT to AI (in Finnish) 24K, online studies
Master of Engineering, from IoT to AI (in Finnish) 22S, online studies
Master of Engineering, From IoT to AI, Lahti
Enrollment
06.05.2024 - 25.08.2024
Timing
26.08.2024 - 29.08.2024
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus
Teaching languages
- Finnish
Seats
10 - 60
Degree programmes
- Master of Engineering, Regenerative Leadership (in Finnish)
- Master’s Degree Programme in Engineering, from IoT to AI (in Finnish)
Teachers
- Minna Asplund
- Henri Koukka
- Erjaleena Koljonen
Scheduling groups
- Luennot 1 (Size: 100. Open UAS: 0.)
Groups
-
TLTIYITT24KV
-
LLPRYASLI23KV
-
LLTIYLDR23SV
-
TLTIYUJT24SV
Small groups
- Lecture 1
Learning outcomes
The student is able to
- examine the properties of the data in terms of further processing
- utilize mathematical methods in data analysis
- utilize a modern statistical tool
- visualize data and analysis in a way that utilizes further processing
- produce a reproducible research
Assessment scale
1-5
Enrollment
06.05.2024 - 30.08.2024
Timing
02.12.2024 - 05.12.2024
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Seats
15 - 35
Degree programmes
- Master’s Degree Programme in Engineering, from IoT to AI (in Finnish)
Teachers
- Matti Welin
- Henri Koukka
Scheduling groups
- Luennot 1 (Size: 100. Open UAS: 0.)
Groups
-
TLTIYITT24KV
Small groups
- Lecture 1
Learning outcomes
Student is able to
- identify digital twin operation principles and application areas
- identify game-like activities and possibilities in the digital twin operational environment
- identify game engine possibilities in the digital twins' presentation layer
- implement simple digital twin using modern game engine
Assessment scale
1-5
Enrollment
06.05.2024 - 30.08.2024
Timing
04.11.2024 - 07.11.2024
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Seats
5 - 40
Degree programmes
- Master’s Degree Programme in Engineering, from IoT to AI (in Finnish)
Teachers
- Matti Welin
- Minna Asplund
- Rami Viksilä
Scheduling groups
- Luennot 1 (Size: 100. Open UAS: 0.)
Groups
-
TLTIYITT24KV
Small groups
- Lecture 1
Learning outcomes
The student is able to
- identify the key features of neural networks and deep learning
- study hyperparameters, activation functions, and neural network topology
- handle hidden layers as well as predict using existing data
- take into account usage of resources and the ethical aspects of artificial intelligence
Assessment scale
1-5
Enrollment
06.05.2024 - 30.08.2024
Timing
30.09.2024 - 03.10.2024
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Seats
5 - 40
Degree programmes
- Master’s Degree Programme in Engineering, from IoT to AI (in Finnish)
Teachers
- Matti Welin
- Minna Asplund
- Rami Viksilä
Scheduling groups
- Luennot 1 (Size: 100. Open UAS: 0.)
Groups
-
TLTIYITT24KV
Small groups
- Lecture 1
Learning outcomes
The student is able to
- take advantage of both supervised and unsupervised machine learning in a functional way
- implement the training of the machine learning model
- utilize data-driven decision making
- compare hardware, software and development environments with different applications utilizing machine learning
Assessment scale
1-5