Master’s Degree Programme in Engineering, from IoT to AI
Master of Engineering, from IoT to AI 23S, online studies
Master of Engineering, from IoT to AI 24K, online studies
Master of Engineering, from IoT to AI 22S, online studies
Master of Engineering, From IoT to AI, Lahti
Enrollment
15.05.2023 - 01.09.2023
Timing
27.11.2023 - 30.11.2023
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
10 - 40
Degree programmes
- Complementary competence and optional courses, Masters
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Henri Koukka
- Erjaleena Koljonen
- Minna Asplund
Scheduling groups
- Verkkoluento 1 (Size: 0. Open UAS: 0.)
Groups
-
TLTIYITT23SV
Small groups
- Verkkoluento 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
20.11.2023 - 05.01.2024
Timing
08.01.2024 - 31.07.2024
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
- Complementary competence and optional courses, Masters
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Matti Welin
- Henri Koukka
Scheduling groups
- Luennot 1 (Size: 0. Open UAS: 0.)
Groups
-
TLTIYITT23SV
-
TLTIYTO23H
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
20.11.2023 - 05.01.2024
Timing
11.03.2024 - 14.03.2024
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
Teachers
- Matti Welin
- Minna Asplund
- Rami Viksilä
Scheduling groups
- Verkkoluento 1 (Size: 500. Open UAS: 0.)
Groups
-
TLTIYITT23SV
Small groups
- Online 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
15.05.2023 - 01.09.2023
Timing
16.10.2023 - 19.10.2023
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
Degree programmes
- Complementary competence and optional courses, Masters
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Matti Welin
- Tommi Veijalainen
Scheduling groups
- Luennot 1 (Size: 0. Open UAS: 0.)
Groups
-
TLTIYITT23SV
Small groups
- Luennot 1
Learning outcomes
The student is able to
- understand the contribution of IoT to the significant increase in the amount of data, understand the nature of sensor data and know the basic principles of data processing at the sensor level
- understand the basic structure of IoT devices
- store measurement results in a database and understand the usability of time series databases
- transfer the measurement results to the cloud service using the standard IoT protocol
- describe the structures of different IoT network architectures and their integration into larger information systems
- take into account the specific security risks of IoT technologies
Assessment scale
1-5
Enrollment
20.11.2023 - 12.01.2024
Timing
13.05.2024 - 16.05.2024
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
Teachers
- Matti Welin
- Tommi Veijalainen
- Juha Hyytiäinen
Scheduling groups
- Luennot 1 (Size: 500. Open UAS: 0.)
Groups
-
TLTIYITT24KV
Small groups
- Lecture 1
Learning outcomes
The student is able to
- understand the contribution of IoT to the significant increase in the amount of data, understand the nature of sensor data and know the basic principles of data processing at the sensor level
- understand the basic structure of IoT devices
- store measurement results in a database and understand the usability of time series databases
- transfer the measurement results to the cloud service using the standard IoT protocol
- describe the structures of different IoT network architectures and their integration into larger information systems
- take into account the specific security risks of IoT technologies
Assessment scale
1-5
Enrollment
20.11.2023 - 05.01.2024
Timing
15.01.2024 - 18.01.2024
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
Teachers
- Matti Welin
- Minna Asplund
- Rami Viksilä
Scheduling groups
- Verkkoluento 1 (Size: 500. Open UAS: 0.)
Groups
-
TLTIYITT23SV
Small groups
- Online 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
Enrollment
15.05.2023 - 31.07.2024
Timing
01.08.2023 - 31.07.2024
Number of ECTS credits allocated
10 op
Virtual portion
10 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Degree programmes
- Master of Engineering, Regenerative Leadership
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Mirka Airesvuo
- Minna Asplund
- Lea Heikinheimo
- Mirva Rainio
Groups
-
TLTIYITT23SV
-
TLTIYUJT23SV
Learning outcomes
The student is able to
- describe the objectives and core contents of their thesis
- plan and describe the stages of the thesis process
- take into account the possible research permit and copyright issues.
Assessment scale
1-5
Enrollment
20.11.2023 - 31.12.2024
Timing
01.01.2024 - 31.12.2024
Number of ECTS credits allocated
10 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Degree programmes
- Master’s Degree Programme in Engineering, from IoT to AI
- Master's Degree Programme in Urban Sustainability
Teachers
- Eeva Aarrevaara
- Minna Asplund
- Paul Carroll
- Anne-Marie Tuomala
- Lea Heikinheimo
- Mirva Rainio
Scheduling groups
- Verkkoluento 1 (Size: 100. Open UAS: 0.)
- Seminaari 1 (Size: 100. Open UAS: 0.)
Groups
-
TLTIYITT24KV
-
TLTIYKKY24KV
Small groups
- Online lecture 1
- Seminar 1
Learning outcomes
The student is able to
- describe the objectives and core contents of their thesis
- plan and describe the stages of the thesis process
- take into account the possible research permit and copyright issues.
Assessment scale
1-5
Enrollment
15.05.2023 - 31.07.2024
Timing
01.08.2023 - 31.07.2024
Number of ECTS credits allocated
20 op
Virtual portion
20 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Degree programmes
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Minna Asplund
- Lea Heikinheimo
- Mirva Rainio
Scheduling groups
- Verkkoluento 1 (Size: 500. Open UAS: 0.)
Groups
-
TLTIYITT23SV
-
TLTIYUJT23SV
Small groups
- Online lecture 1
Learning outcomes
The student is able to
- implement the thesis on the basis of an approved thesis plan
- present the results or output of their thesis
- report on their thesis in writing in accordance with the thesis guidelines of LAB University of Applied Sciences
- as a maturity test, write a blog post, a press release or an article.
Assessment scale
1-5
Enrollment
20.11.2023 - 31.12.2024
Timing
01.01.2024 - 31.12.2024
Number of ECTS credits allocated
20 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Degree programmes
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Minna Asplund
Scheduling groups
- Seminaari 1 (Size: 500. Open UAS: 0.)
Groups
-
TLTIYITT24KV
Small groups
- Seminar 1
Learning outcomes
The student is able to
- implement the thesis on the basis of an approved thesis plan
- present the results or output of their thesis
- report on their thesis in writing in accordance with the thesis guidelines of LAB University of Applied Sciences
- as a maturity test, write a blog post, a press release or an article.
Assessment scale
1-5
Enrollment
15.05.2023 - 01.09.2023
Timing
04.09.2023 - 15.12.2023
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
Degree programmes
- Complementary competence and optional courses, Masters
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Matti Welin
- Rami Viksilä
Scheduling groups
- Verkkoluento 1 (Size: 0. Open UAS: 0.)
Groups
-
TLTIYITT23SV
Small groups
- Verkkoluento 1
Learning outcomes
The student knows
- the basics of using the command line in the development and production environment of digital services
- how to compare and leverage virtualization as part of resource-efficient design and implementation of digital services
- how to design and implement a digital service using virtualization and cloud services on a selected platform
- how to discuss and justify the choice of virtualization and cloud services as a platform for digital services.
Assessment scale
1-5
Enrollment
20.11.2023 - 12.01.2024
Timing
05.02.2024 - 08.02.2024
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
- Complementary competence and optional courses, Masters
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Matti Welin
- Rami Viksilä
Scheduling groups
- Verkkoluento (Size: 500. Open UAS: 0.)
Groups
-
TLTIYITT24KV
-
TLTIYTO23H
Small groups
- Online lecture
Learning outcomes
The student knows
- the basics of using the command line in the development and production environment of digital services
- how to compare and leverage virtualization as part of resource-efficient design and implementation of digital services
- how to design and implement a digital service using virtualization and cloud services on a selected platform
- how to discuss and justify the choice of virtualization and cloud services as a platform for digital services.
Assessment scale
1-5
Enrollment
06.05.2024 - 30.08.2024
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
- Master’s Degree Programme in Engineering, from IoT to AI
Teachers
- Henri Koukka
- Minna Asplund
- 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
Mode of delivery
Contact teaching
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
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
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
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