Ages 15–18
AI Product Development Course for Ages 15–18
Participants use AI coding tools with product thinking, code literacy, testing and security—not as an unchecked shortcut.
A short note for parents
Why AI-assisted coding?
The era of relying only on traditional coding methods is ending. AI can now generate code; the future skill is defining the right problem, directing AI, understanding and testing its output, and turning it into a safe product. This program teaches students not only to code, but to build products responsibly with AI.
Instructor
Direct, hands-on learning with Onur Altınsoy
Onur Altınsoy has 15 years of software industry experience. He worked for a total of 10 years as a Software Specialist within Karbel Holding and iLab Holding, followed by five years as Software Director at iLab Holding, leading technical teams and digital product delivery.
- 15 years of software and product development experience
- 10 years as a Software Specialist within Karbel Holding and iLab Holding
- 5 years as Software Director and team leader at iLab Holding
Program outcomes
A working product ready for a portfolio
Product thinking
Define a problem, target user and achievable minimum product scope.
AI-assisted development
Use a coding agent while reading, directing and correcting generated code.
Technical foundations
Experience frontend, APIs, data, authentication, GitHub and deployment.
Portfolio and presentation
Present the live product, source code and key product decisions during demo day.
Four-week curriculum
Validate, build, test and publish the idea
- 01
Problem and product scope
User need, value proposition and an achievable MVP definition.
- 02
Interface and user flow
Screens, component thinking and a usable product journey.
- 03
AI coding agents and code literacy
Context, task breakdown, code review and version control.
- 04
Frontend development
Responsive interfaces, state and user interactions.
- 05
APIs and data
External services, data flow and basic persistence.
- 06
Authentication and security
Identity, secrets, permissions and responsible AI use.
- 07
Testing and deployment
Debugging, edge cases, performance and production release.
- 08
Portfolio and demo day
README, product story, live demo and a roadmap for iteration.
Learning model
Short theory, long building time
- A working part of the product every week
- Live coding and screen sharing
- Code and product feedback
- GitHub, deployment and portfolio support
Program options
Group program or one-to-one mentorship
Group of up to 10
Team energy, peer feedback and structured weekly deliveries.
- 6 live lessons
- Weekly product deliveries
- Code and product review
- Demo day and portfolio output
One-to-one mentorship
Personalized product scope, technical guidance and flexible pacing.
- 6 one-to-one sessions
- Personal product roadmap
- Feedback between sessions
- GitHub and deployment support
Third-party paid AI tools are not included; any required tools are disclosed before enrollment.
Responsible development
AI creates; the student verifies
Every technical decision addresses data privacy, source checking, security, licensing and verification of AI output.
Frequently asked questions
Before joining the program
Is coding experience required?
It is not required. Students with some experience can choose a broader project; level is assessed during the introduction call.
What will be built by the end?
Each student completes a working, published digital product that can be presented through GitHub.
Which tools will be used?
A modern code editor, GitHub, a deployment service and AI tools appropriate to age and account requirements.
Can it be used in a university portfolio?
Yes. The program focuses on an explainable portfolio output with a README, live demo and product story.
Let's clarify the project idea and learning goal
Use the free introduction call to assess level, product idea and the right group or mentorship format.