Embedded Files
October–November, 2026
Problem Solving Through Generative AI
Problem Solving Through Generative AI
➤ Intended for: bachelor and master level EU students
➤ ECTS credits: 3
➤ Contact email: anne.uukkivi@tktk.ee
Key Dates
Key Dates
Online sessions:
19 October 2026
21 October 2026
22 October 2026
Intensive week in Tallinn:
2–6 November 2026
Location:
TTK University of Applied Sciences, Tallinn, Estonia
The BIP is intended for bachelor and master level students from different study fields who are interested in generative AI, problem-solving, innovation, teamwork, and real-world business challenges.
Students will work in international and interdisciplinary teams on challenges proposed by businesses. They will analyse real-world problems, explore meaningful opportunities for AI, and design, build and test practical AI-supported solutions.
Expected Learning Outcomes
Expected Learning Outcomes
By the end of the BIP, participants will be able to:
understand the principles, possibilities, and limitations of generative AI;
use different AI tools purposefully and responsibly for problem-solving;
analyse and justify the use of AI in learning and work contexts;
analyse ethical, social, and ecological dimensions of generative AI;
identify when and how to implement AI solutions in different business cases;
envision and build generative AI-based solutions.
General concept and organisation:
General concept and organisation:
The BIP focuses on the practical use of artificial intelligence for solving real-world business challenges. Students work in international and interdisciplinary teams on challenges proposed by partner organisations.
During the programme, teams analyse existing processes, identify problems and meaningful opportunities for AI, develop and compare possible solution concepts, and design, build and test an AI-supported prototype.
The programme combines:
generative AI tools and AI-assisted building;
design thinking and problem-solving;
international and interdisciplinary teamwork;
real-world university-business collaboration;
responsible AI design.
Students consider not only how AI can be used, but also whether and where it creates meaningful value. When developing their solutions, they examine feasibility, risks, ethical and social dimensions, sustainability, relevant stakeholders, and potential implementation barriers.
Preliminary agenda 📅
Preliminary agenda 📅
The schedule is subject to changes.
Online Session 1 – Kick-off and Team Formation
Online Session 1 – Kick-off and Team Formation
19 October 2026
Welcome and introduction to the BIP journey and deliverables
Meet the international team and mentors
Team building and collaborative expectations
Develop the Team Charter
Introduction to the challenge
Online Session 2 – Core Skills and Tools
Online Session 2 – Core Skills and Tools
21 October 2026
Core skills for approaching generative AI
Generative AI tools and their purposeful use
AI-assisted problem-solving and building
Preparation for challenge work
Online Session 3 – Responsibility by Design
Online Session 3 – Responsibility by Design
22 October 2026
Explore different dimensions of AI implementation
Ethical, social and sustainability considerations
Visualise and clarify the problem
Prepare for the intensive week
On-site week in Tallinn
Monday – Understand the Workflow
Monday – Understand the Workflow
Where exactly is the problem?
2 November 2026
Reconnect with the team and revisit the Challenge Brief
Map the current process
Identify key pain points, assumptions and open questions
Share findings and receive feedback
Tuesday – Explore and Decide
Tuesday – Explore and Decide
Where could AI create meaningful value?
3 November 2026
Explore AI capabilities relevant to the challenges
Identify possible AI opportunities and alternative solution directions
Develop and compare solution concepts
Consider value, feasibility and risks
Select and refine the direction for prototyping
Wednesday – Design and Build
Wednesday – Design and Build
How should the solution work in practice?
4 November 2026
Explore AI solution architecture, prompting and responsible design
Develop the prototype with teacher support
Test and refine the solution
Present an interim demonstration and receive feedback
Thursday – Present the Prototype
Thursday – Present the Prototype
How does our solution stand up to external feedback?
5 November 2026
Final preparation at Tehnopol
Prototype presentations and demonstrations
Discussion and feedback with external experts
Team debrief and analysis of feedback
Friday – Feedback and Reflection
Friday – Feedback and Reflection
What did we learn and what would we do next?
6 November 2026
Review feedback from the prototype presentations
Reflect on the design process, collaboration and learning
Complete the individual reflection / AI Exploration Log
Programme feedback and closing discussion
__________
NB! Please contact the Erasmus coordinator of your home university to discuss details for funding before you register.
__________
Page updated
Report abuse