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Master’s Degree Programme in Technological Transformation Leadership (Technology)

Degree:
Master of Engineering

Degree title:
Master of Engineering

Credits:
60 ects

Technological Transformation Leadership 25S, online studies
Code
(TLTIYTTL25SV)
Enrollment

07.05.2025 - 31.08.2025

Timing

28.10.2025 - 31.12.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

Faculty of Technology (LAB)

Campus

E-campus

Teaching languages
  • English
Seats

0 - 60

Degree programmes
  • Master’s Degree Programme in Technological Transformation Leadership (Social and Health Care)
  • Master’s Degree Programme in Technological Transformation Leadership (Technology)
Teachers
  • Arja-Tuulikki Malin
Groups
  • TLTIYTTL25SV
    Master’s Degree Programme in Technological Transformation Leadership 25SV Lahti
  • HLTIYTTL25SV
    Master’s Degree Programme in Technological Transformation Leadership 25SV Lahti

Learning outcomes

The student is able to
- effectively analyze organizational knowledge to drive innovation and improve decision-making
- utilize change management frameworks and models
- develop skills to implement change initiatives, focusing on overcoming resistance and fostering a culture of agility
- implement strategies for effective communication, stakeholder engagement, and addressing resistance to change

Implementation and methods of teaching

Mandatory pre-assignment for the course. Virtual instruction via Zoom ( 3 x 4 h). Essay (8-10 pages).

Timing and attendance

Mandatory pre-assignment 28.10-9.11.2025
Virtual instruction via Zoom 11.11, 18.11 ja 15.11 klo 9-13 - no mandatory attendance
Essay due 31.12.

Learning material and recommended literature

In Moodle

Alternative completion methods

-

Working life cooperation

-

Exam retakes

according to the degree regulations

Learning environment

Zoom, Moodle.

Student time use and work load

Virtual instruction 3x4h
Independent studies before instruction 20h
Pre-assignment and essay 80-100h

Contents

Theory on change management and knowledge management. Analysis of organizational knowledge to drive innovation and decision-making. Change management frameworks and models. Implementing change initiatives, focusing on overcoming resistance and fostering a culture of agility. Strategies for effective change management.

Additional information for students: previous knowledge etc.

-

Assessment scale

1-5

Failed (0)

The student uses some of the key concepts of and knows the theoretical foundations, but does not show skills for applying it. The student refers in the essay mainly to the material presented in class, but has not increased his or her own knowledge with other source material.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to apply theoretical knowledge of in describing and evaluating the operations of various organizations. The student uses the key concepts and theories of change and knowledge management. The student uses relevant published sources in the essay.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to apply theoretical knowledge in describing and evaluating the operations of various organizations. The student uses key concepts and demonstrates understanding and competence in theory. The student is also familiar with research.

Assessment criteria: level 5 (assessment scale 1–5)

The student is able to apply theoretical knowledge critically in describing and evaluating the operations of various organizations. The student uses key concepts skillfully and demonstrates a deep understanding of theory. The student is also familiar with international research knowledge in a broad and in-depth manner.

Enrollment

07.05.2025 - 31.08.2025

Timing

01.08.2025 - 31.12.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

Faculty of Technology (LAB)

Campus

E-campus

Teaching languages
  • English
Degree programmes
  • Master’s Degree Programme in Technological Transformation Leadership (Technology)
Teachers
  • Mika Lohtander
Scheduling groups
  • Scheduling group (Size: 0. Open UAS: 0.)
Groups
  • TLTIYCES25SV
    Master’s Degree Programme in Circular Economy Solutions 25SV Lahti
  • TLTIYTTL25SV
    Master’s Degree Programme in Technological Transformation Leadership 25SV Lahti
  • TLABYTO25-26E
    Complementary competence (Master's) 2025-2026, Faculty of Technology
Small groups
  • Scheduling group

Learning outcomes

The student is able to
- examine the role of emerging technologies in enabling innovation
- consider scalability in the design of technology-enabled innovations
- apply technology-enabled innovations in developing business models for better value creation
- evaluate the potential impacts of emerging technologies on business and society

Implementation and methods of teaching

The course is conducted online. The course includes a preliminary assignment, online lectures, and group assignments during online lectures. The exercises are done in groups of 2-3 people. A assignment presentation is returned from the exercises, which is made available to the entire implementation.

Timing and attendance

The course pre-assignment will be available on 29.10. The pre-assignment must be returned to the course assignment return area by 14.11. at the latest.

The topics for the practice assignment will be visible on 17.11. The practice assignment must be returned by 18.11.
The online lectures are on 19.11., 3.12. and 17.12.

The student must be present and participate in the teaching events during the online lectures. One absence is allowed if agreed in advance.

Learning material and recommended literature

The online services of the LUT/LAB science library, and in particular the Scopus-AI service, are used as learning materials.

Alternative completion methods

The course has no optional completion methods. The course must be completed in one implementation.

Working life cooperation

The issues and themes covered in the course follow themes that arise directly from working life.

Exam retakes

The course must be completed in one session. There is no separate exam opportunity for the course.

Student time use and work load

Pre-requisites 27h.
Lectures and preparation for them 27h.
Practical work 81h.

Contents

This course provides an in-depth overview at emerging technologies and their role in creating innovative solutions across industries. The course examines technologies such as artificial intelligence, machine learning, robotics, 5G, and other emerging innovations, and their applications in business and society.

During the course, students will learn how emerging technologies can create new business opportunities, improve efficiency, and solve previously intractable problems. Students will also learn to evaluate the potential and practical applications of these technologies, as well as their impact on organizations and society at large.

Course objectives:
• Understand the role and importance of emerging technologies in creating innovative solutions.
• Study the basic principles of the latest technologies and their application possibilities.
• Gain an understanding of innovative solutions used across industries.
• Develop the ability to evaluate the business and ethical implications of new technologies.

Additional information for students: previous knowledge etc.

There are no specific prerequisites for the course, but basic knowledge of business and technology fundamentals is an advantage.

Assessment criteria

Participation and pre-assignment (50%): Active participation in lectures and seminars, as well as group assignments that measure collaboration skills and practical application of technology.

Practical work (50%): Designing and presenting an innovative technology solution as a practical application, where students can demonstrate their in-depth knowledge and creativity.

The assessment is based on a scale of 0–5, where 0 is failed and 5 is excellent.

Assessment scale

1-5

Failed (0)

Description: The student has not met the course requirements and/or has fallen behind on important assignments or exams. The assessment criteria have not been met, and the student has not demonstrated sufficient competence during the course. For example: has not participated sufficiently in learning tasks, has not completed required assignments or exams.

Examples:
• Has not participated sufficiently in lectures or other educational events.
• Has not returned assignments by the due date.
• Has not demonstrated understanding of the key topics of the course

Assessment criteria: level 1 (assessment scale 1–5)

Description: The student has completed the course assignments, but the knowledge is weak and the requirements are only partially met. The student demonstrates basic understanding, but the key concepts and skills of the course have not been mastered in sufficient depth. The student still needs significant support and guidance.

Examples:
• Only some of the assignments have been completed and returned on time.
• The student has not actively participated in group work.

Assessment criteria: level 3 (assessment scale 1–5)

Description: The student has completed the course well and demonstrates a clear understanding of the key topics of the course. He/she is able to apply the skills and concepts learned in a variety of situations and produce high-quality answers. Although there may be minor shortcomings, the student has nevertheless shown good understanding and commitment.

Examples:
• Assignments have been returned on time and have good justifications and correct answers.
• Actively participated in group work and presented their own ideas.

Assessment criteria: level 5 (assessment scale 1–5)

Description: The student has exceeded the requirements of the course and demonstrates exceptional competence and depth of understanding. He/she is able to apply what he/she has learned innovatively and creatively to a variety of contexts. The student also demonstrates excellent skills in working independently and in a group. The course content has been mastered perfectly.

Examples:
• The assignments are exceptionally well done, and they involve deep reflection and analysis.
• In group work, the student has demonstrated exceptional leadership and creativity, and his/her contribution has been significant.

Enrollment

07.05.2025 - 31.08.2025

Timing

03.11.2025 - 06.11.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Faculty of Technology (LAB)

Campus

E-campus

Teaching languages
  • English
Degree programmes
  • Master’s Degree Programme in Technological Transformation Leadership (Technology)
Teachers
  • Matti Welin
  • Rami Viksilä
Scheduling groups
  • Verkkoluento 1 (Size: 500. Open UAS: 0.)
Groups
  • TLTIYTTL25SV
    Master’s Degree Programme in Technological Transformation Leadership 25SV Lahti
  • TLABYTO25-26E
    Complementary competence (Master's) 2025-2026, Faculty of Technology
Small groups
  • Online lecture 1

Learning outcomes

The student is able to
- manage data collection and employ standard protocols for data transfer to a cloud service
- implement a data storage solution leveraging virtualization and cloud-based services
- conduct comparative analysis of data processing, transfer, and storage alternatives within the context of a data pipeline implementation

Assessment scale

1-5

Enrollment

07.05.2025 - 31.08.2025

Timing

27.08.2025 - 15.10.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

Faculty of Technology (LAB)

Campus

E-campus

Teaching languages
  • English
Degree programmes
  • Master’s Degree Programme in Technological Transformation Leadership (Social and Health Care)
  • Master’s Degree Programme in Technological Transformation Leadership (Technology)
Teachers
  • Matti Welin
  • Tommi Veijalainen
  • Annamaija Id-Korhonen
  • Rami Viksilä
Scheduling groups
  • Verkkoluento 1 (Size: 500. Open UAS: 0.)
Groups
  • TLTIYTTL25SV
    Master’s Degree Programme in Technological Transformation Leadership 25SV Lahti
  • HLTIYTTL25SV
    Master’s Degree Programme in Technological Transformation Leadership 25SV Lahti
Small groups
  • Online lecture 1

Learning outcomes

The student is able to
- evaluate the influence of emerging technologies on their specific discipline and the broader society
- analyze key megatrends and their connections to technological development
- apply diverse technologies to address complex practical challenges
- develop informed perspectives on the future technological evolution and its potential implications

Implementation and methods of teaching

Moodle learning platform and online lectures in Zoom platform.

Timing and attendance

Autumn 25
Online lectures 27.8.- 15.10. on Wednesdays at 9-13 o'clock. In between the assignments.

Learning material and recommended literature

The learning materials and literature will be shown in Moodle platform.

Alternative completion methods

Recognition of prior learning with suitable method

Learning environment

Moodle platform and online lectures.

Student time use and work load

Online lectures 27.8.- 15.10. on Wednesdays at 9-13 o'clock. In between the assignments.

Contents

Evaluatin of the influence of emerging technologies on their specific discipline and the broader society
Analysis of the key megatrends and their connections to technological development
Application of diverse technologies to address complex practical challenges
Development of informed perspectives on the future technological evolution and its potential implications.

Megatrends 2050 affecting technological transformation, Quantum computers and computing, LLM basics, Prompt engineering, LLM technical comparison, LLM fine-tuning, RAG, agent basics and NotebookLM an ethics, technological megatrends in social and health care.

Assessment criteria

Each lecturer has its own assessment task or exam.

Assessment scale

1-5

Failed (0)

Student does not reach the objectives of the course.

Can't solve science problems during the course.

Assessment criteria: level 1 (assessment scale 1–5)

Student does reach some of the objectives, expected knowledge and skills in this course course.

Can apply the learned techniques to science problems presented during the course. Can solve science problems

Assessment criteria: level 3 (assessment scale 1–5)

Student can partly reach the learning objectives and expected knowledge, skills, critical thinking and synthesize information to solve complex problems in this course course.

Can solve science problems during the course in a versatile way. Show active participation and understanding during the course

Assessment criteria: level 5 (assessment scale 1–5)

Student can fully reach the learning objectives and expected knowledge, skills critical thinking and synthesize information to solve complex problems in this course.

Can solve all or almost all science problems during the course. Show good command of course related facts and can apply them during the course.