Service Design: Driving Growth in Exports: Co-Developing AI-Powered Continuous Learning Solution for Global Exporters (15 cr)

Learning outcomes

The student is able to
- plan, implement and evaluate a Service Design project with service design methods
- develop sustainable practices in organisations

Location and time

Please refer to the Timetable Engine at https://lukkarit.laurea.fi/ for the schedule information. Laurea reserves the right to modify the timetable.

Materials

The source materials needed for the subject area of the project are selected separately after the project assignment.

Teaching methods

In the project, students will develop and implement a custom Generative Pre-trained Transformer (GPT) model tailored specifically for the Finnish export industry. Building upon existing AI technologies, the project will focus on refining the GPT model to meet the unique needs and challenges faced by Finnish export companies.

GPT Model Development: Collaborate with AI experts to customize and train a GPT model that understands the language and intricacies of the Finnish export industry. This will involve fine-tuning the model's language capabilities and domain-specific knowledge.

Educational Outreach: Devise strategies to educate Finnish export companies on the benefits and applications of the custom GPT model. This may include organizing workshops, webinars, and informational sessions to showcase the capabilities of AI in enhancing business operations.

Expected Outcomes:
By the end of the project, students will have successfully developed and implemented a custom GPT model tailored for Finnish export companies. Through educational outreach efforts, participating companies will be empowered to harness the power of AI to streamline their operations, enhance decision-making, and drive growth in the global marketplace. Additionally, the project will contribute to advancing AI adoption and innovation within the Finnish export industry, positioning companies for success in an increasingly competitive global landscape.


The project is completed in cooperation with a working life partner in a P2P learning environment. Working life partner is Laurea, SURE program.

The enrolled students will develop their competencies related to the study in question during this project implementation.

Daytime learning:
An independently studied part (in Canvas) supports the project implementation, but it is important to take part in project teamwork and guidance on campus according to schedule. Studying requires active participation and commitment to interactive project work. You will receive individual feedback for assignments from the teacher, and working life or peer feedback are also utilised.

Project’s guidance and working sessions can be viewed in Timetable Engine / Tuudo. Communication practices are agreed on a project-specific basis.

Laurea reserves the right to make changes.

Quality of implementation has been evaluated and self-evaluation report is available Teams.

Employer connections

Working life partner: Laurea, SURE program.

Exam schedules

Kick-Off (mandatory participation): 5th of Sep. Exact time will be announced.

It is compulsory to participate in the project kickoff meeting so that everyone participating in the project will receive the information on the project task.

Project guidance is offered on a weekly basis. The student can compare the available guidance sessions in Timetable Engine and select those projects/studies that do not overlap.

According to the degree regulations (2024) "the student must be present at the first contact lesson or notify the teacher in charge of their absence to confirm their participation in the study. Registration will be rejected if the student does not report their absence at the start of the study or the reason for the absence cannot be considered justified. Another student can be taken in their place. In project studies the first contact lesson is the first meeting of the project team and guiding lecture(s).

Completion alternatives

According to the degree regulations (2024), "Students are entitled to apply for recognition of prior learning regardless of where, when and how the competence has been acquired. ... At Laurea, there are two different procedures for the recognition and accreditation of prior learning: a) accreditation of prior learning (competence acquired in higher education studies at another institution) and b) demonstration of competence (competence acquired in other ways). The recognition and accreditation of prior learning is initiated by the student themselves. The student is responsible for demonstrating and verifying their competence. The student is entitled to guidance for the recognition and accreditation of their competence." Further information in the student intranet.

You may also assess work-based learning as a way to acquire the competence needed. Read more in the student intranet.

Student workload

Workload of the study is measured in a way that to acquire the goal competence of the study, one credit corresponds to an average of 26.7 hours of work done by the student. The actual time needed varies e.g. according to prior competence.

The weekly project meeting on campus is mandatory!

Also, please note the student will participate in a "Hackathlon"-event in October. More details will follow, but the event will be concidered to be worth 3 study credits and will replace workload of one theory base.

Content scheduling

Aims of the project:

Develop a custom GPT model for the Finnish Export Industry

Find ways to educate the exporters to the custom GPT program.

Evaluation scale

H-5

Further information

The study unit corresponds to the requirements of Bachelo's level education.

This study implementation is a P2P project meaning that the project is completed in a small group and guided by a teacher. Participating in the project requires attendance in the project guidance meetings and group meetings.

The prerequisite for participation is always that the possible competence prerequisites according to the curriculum (previous study or similar competence) are fulfilled. The student is responsible for taking into account the prerequisite conditions.

The quality of the study unit implementation has been assessed and the self-evaluation report is available for example in Canvas or Teams.