Developing Professional Competencies 1 (3cr)

Evaluation scale

H-5

Content scheduling

Introduction session + AI training: Tue 4th Nov 2pm-3.30pm (online) Hackathon event: Thu 13th Nov 8am-17pm (Helsinki, Helsinki XR Center)

Objective

During the course the student develops their professional competences in accordance with the objectives of their personal study plan. The specific learning objectives are agreed on an individual basis for each course implementation by the student or student group and the teacher of the course.

Methods of completion

Contact, Contact blended, Online, Online blended, Virtual. The course features project-based work done either individually or in a group. The course may also include work-based learning and demonstrations.

Methods of completion

In this course the student tailors the course contents on an individual / project basis. The course flexibly combines different implementation methods and contents.

Content

The contents are planned to fit the implementation and student needs. For example: - A commissioned project - Planning and/or attending an event - Participating in a competition - Demonstrating and strengthening competences in accordance with a specific standard or certificate

Materials

Provided during the meetings.

Teaching methods

AI Hackathon (3 ECTS, 91 hours) Course Description: This interdisciplinary course brings together students from Haaga-Helia, Laurea and Metropolia to explore the potential of artificial intelligence through an intensive hackathon format. The course combines preparatory learning, practical experimentation, and reflective analysis, enabling students to strengthen both their technological and collaborative skills. Before the hackathon, students participate in an AI training session that introduces key concepts, tools, and applications relevant to the challenges they will face. Students also complete a pre assignment designed to encourage critical thinking about AI and its role in business and society. The core of the course is the AI Hackathon, where student teams develop innovative solutions to real-world company cases. Working under time pressure, students learn to apply AI methods creatively, collaborate across disciplines, and present their ideas effectively. Following the hackathon, teams finalise their case ideas and reflect on their learning through a structured assignment. This reflection allows students to connect their practical experience with theoretical perspectives and to evaluate their personal and team performance in the innovation process. Learning Outcomes: Upon completing the course, students will be able to: • Understand the fundamentals of artificial intelligence and its potential applications. • Apply AI concepts and tools to real-life problem-solving in a hackathon setting. • Collaborate effectively in interdisciplinary and cross-institutional teams. • Develop and present innovative case solutions under time constraints. • Reflect critically on their learning process and outcomes in the context of AI-driven innovation. Assessment: Assessment is based on participation in the AI training and hackathon, the preparatory task, the finalised case solution, and the reflective learning assignment. The course is graded on a pass/fail basis.

Exam schedules

No exam

International connections

International Hackathon event

Student workload

Pre assignment and learning, group report and individual reflection.

Qualifications

Prerequisites are determined for each course implementation.