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New TechnologiesLaajuus (5 cr)

Code: TLTT4500

Credits

5 op

Teaching language

  • Finnish
  • English

Responsible person

  • Pasi Poutiainen

Objective

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Assessment criteria, satisfactory (1)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Assessment criteria, good (3)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Assessment criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 19.05.2025

Number of ECTS credits allocated

5 op

Virtual portion

2.5 op

Mode of delivery

50 % Face-to-face, 50 % Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

20 - 25

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • TLS23SMM
    Logistiikka - tutkinto-ohjelma (AMK)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 30.04.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

20 - 58

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Scheduling groups
  • TLS23SA (Capacity: 35. Open UAS: 0.)
  • TLS23SB (Capacity: 35. Open UAS: 0.)
Groups
  • TLS23S1
    Logistiikka - tutkinto-ohjelma (AMK)
Small groups
  • TLS23SA
  • TLS23SB

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments and possible laboratory tasks.

The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.

The course also includes larger project work

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 30.04.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • English
Seats

20 - 44

Degree programmes
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Groups
  • TLP25VK
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP24VS
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP23S1
    Bachelor's Degree Programme in Purchasing and Logistics Engineering

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Timing

23.09.2024 - 15.12.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Logistics
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Groups
  • ZJAJ24KTMJ
    Avoin Amk,Materiaalivirtojen johtaminen, monimuoto, TEKN

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Toteutus on tarkoitettu avoimen ammattikorkeakoulun Materiaalivirtojen johtamisen opiskelijoille. Se sisältää opetuskertoja (verkossa), videoluentoja, sekä omatoimisesti tai pienryhmissä verkossa tehtäviä oppmistehtäviä ja mahdollisen tenti.

Toteutuksella tehtään myös yks laajempi projektityö, jossa innovoidaan soveltaen erilaisia uusia teknologioita.

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.08.2024 - 22.08.2024

Timing

26.08.2024 - 18.12.2024

Number of ECTS credits allocated

5 op

Virtual portion

2.5 op

Mode of delivery

50 % Face-to-face, 50 % Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

20 - 25

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • TLS23KMM
    Logistiikka - tutkinto-ohjelma (AMK)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.08.2024 - 22.08.2024

Timing

26.08.2024 - 18.12.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

10 - 15

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • UTIVERKKO
    Institute of New Industry, online learning (mechanical, logistics and civil engineering)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

The course also includes larger project work

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Toteutuksen aktiviteettien arviointipisteet lasketaan yhteen. Pisteiden kokonaismäärä määrittelee lopullisen arvioinnin. Maksipistemäärä on 100p ja läpäisyvaatimus on 50p. Arvosanataulukko pisterajoineen esitetään tarkemmin toteutuksen oppimistilassa.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 19.05.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • UTIVERKKO
    Institute of New Industry, online learning (mechanical, logistics and civil engineering)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

The course also includes larger project work

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 20.05.2024

Number of ECTS credits allocated

5 op

Virtual portion

3 op

Mode of delivery

40 % Face-to-face, 60 % Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • TLS22SMM
    Logistiikka - tutkinto-ohjelma (AMK)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 55

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Scheduling groups
  • TLS22SA (Capacity: 30. Open UAS: 0.)
  • TLS22SB (Capacity: 30. Open UAS: 0.)
Groups
  • TLS22S1
    Logistiikka - tutkinto-ohjelma (AMK)
Small groups
  • TLS22SA
  • TLS22SB

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments and possible laboratory tasks.

The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.

The course also includes larger project work

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

20.11.2023 - 14.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • English
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Groups
  • TLP22S1
    Bachelor's Degree Programme in Purchasing and Logistics Engineering
  • TLP23VS
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP24VK
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Timing

15.09.2023 - 17.12.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Logistics
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Groups
  • ZJA23KTMJ
    Avoin Amk,Materiaalivirtojen johtaminen, monimuoto, TEKN

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Toteutus on tarkoitettu avoimen ammattikorkeakoulun Materiaalivirtojen johtamisen opiskelijoille. Se sisältää opetuskertoja (verkossa), videoluentoja, sekä omatoimisesti tai pienryhmissä verkossa tehtäviä oppmistehtäviä ja mahdollisen tenti.

Toteutuksella tehtään myös yks laajempi projektityö, jossa innovoidaan soveltaen erilaisia uusia teknologioita.

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.08.2023 - 24.08.2023

Timing

04.09.2023 - 15.12.2023

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 15

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • TLS22KMM
    Logistiikan tutkinto-ohjelma (AMK)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.08.2023 - 24.08.2023

Timing

28.08.2023 - 18.12.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 15

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Groups
  • UTIVERKKO
    Institute of New Industry, online learning (mechanical, logistics and civil engineering)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

The course also includes larger project work

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.04.2023 - 30.04.2023

Timing

01.05.2023 - 31.08.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 5

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • LOGRAKVERKKO
    Logistiikan ja rakentamisen verkko-opetus

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

The course also includes larger project work

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.11.2022 - 05.01.2023

Timing

09.01.2023 - 19.05.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 5

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • LOGRAKVERKKO
    Logistiikan ja rakentamisen verkko-opetus

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

The course also includes larger project work

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.11.2022 - 05.01.2023

Timing

09.01.2023 - 19.05.2023

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 55

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Scheduling groups
  • TLS21SA (Capacity: 35. Open UAS: 0.)
  • TLS21SB (Capacity: 35. Open UAS: 0.)
Groups
  • TLS21S1
    Logistiikan tutkinto-ohjelma (AMK)
Small groups
  • TLS21SA
  • TLS21SB

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.

The course also includes larger project work

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.11.2022 - 05.01.2023

Timing

09.01.2023 - 19.05.2023

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • English
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • TLP23VK
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP22VS
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP21S1
    Bachelor's Degree Programme in Purchasing and Logistics Engineering

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.08.2022 - 25.08.2022

Timing

29.08.2022 - 21.12.2022

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 5

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • LOGRAKVERKKO
    Logistiikan ja rakentamisen verkko-opetus

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

The course also includes larger project work

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.08.2022 - 25.08.2022

Timing

29.08.2022 - 21.12.2022

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • TLS21KMM
    Logistiikan tutkinto-ohjelma (AMK)

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments, group assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.
There will be also a larger project work including different new technologies within the given topics

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.03.2022 - 31.05.2022

Timing

01.03.2022 - 31.08.2022

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Logistics
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • LOGAKTIIVI
    Logistiikan aktiivitoteutukset

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.10.2021 - 28.02.2022

Timing

10.01.2022 - 31.05.2022

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 10

Degree programmes
  • Bachelor's Degree Programme in Logistics
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • LOGAKTIIVI
    Logistiikan aktiivitoteutukset

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

The course is implemented virtually, which includes self-study (independent learning tasks or group learning tasks). The course includes possible online laboratory work. Pay attention the start and end times of the course, and returning dates of assignments.

Course assignments are described in the course workspace.

Practical training and working life connections

Seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

Assessment is based on learning assignments.
This course doesn't have an separate exam.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.11.2021 - 23.01.2022

Timing

10.01.2022 - 29.04.2022

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • English
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Purchasing and Logistics Engineering
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Groups
  • TLP20S1
    Bachelor's Degree Programme in Purchasing and Logistics Engineering
  • TLP21VS
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP22VK
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.

Enrollment

01.11.2021 - 09.01.2022

Timing

10.01.2022 - 29.04.2022

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages
  • Finnish
Seats

0 - 60

Degree programmes
  • Bachelor's Degree Programme in Logistics
Teachers
  • Pasi Poutiainen
Teacher in charge

Pasi Poutiainen

Scheduling groups
  • TLS20SA (Capacity: 40. Open UAS: 0.)
  • TLS20SB (Capacity: 40. Open UAS: 0.)
Groups
  • TLS20S1
    Bachelor's Degree Programme in Logistics
Small groups
  • TLS20SA
  • TLS20SB

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.