Initial Pitch
Project phase: Business and Data Understanding
You give your team's first public framing of the project for the client and fellow students: the problem you intend to address, who has it, why machine learning is a plausible approach, and what success looks like in the client's terms rather than technical ones. You sketch the data you expect to need, your main assumptions and risks, and a rough plan for how the team will work, then capture the client's feedback into a shared, written understanding of the project's direction.
Starting Points
Key Points
- Problem-analysis: You clearly distinguish between the main problem and secondary issues, and you show you understand the societal impact of this problem.
- Advice: You don't just present facts; you give convincing advice on why your chosen machine learning approach is the best solution, backed by logical arguments.
- Communication: You adapt your language to your audience. You avoid heavy technical jargon when speaking to the client and focus on the value/outcome, while remaining professional for your peers.
- Planning: You present a realistic roadmap of how your team will organize the work and manage the project process.
- Feedback loop: You actively invite feedback from the client and use it to create a shared, written understanding of the project goals.
- Format: The summary of the pitch is a standalone markdown document, made available in GitLab.