FAQs

AI-Assisted Programming for PhD Researchers

Answers to the questions we hear most often. If yours isn’t here, ask the Oshu chat assistant in the corner of this site, or email me. For install questions, start with the Setup page.

How do I see the slides?

Each lecture links to its slides (a RevealJS deck) from the top-right of the lecture page. In the deck, press E to switch to a print-friendly layout, then use your browser’s Print → Save as PDF to export a copy for offline reading or annotation.

Do I need to pay for anything?

No. The Zed student plan and the Mistral free “Experiment” tier cover everything the course requires. You only incur costs if you later choose to use a paid tool (for example, a paid model plan for your own research after the course).

What if my Zed student verification hasn’t come through?

You are not blocked. Zed’s free tier gives you 2,000 edit-prediction completions per month, and everything else in the course works without the paid plan. Verification is usually completed within 72 hours, so apply early. See Setup.

What if I hit Mistral rate limits during class?

Tell me. A backup key pool exists for use during the workshop, so a rate limit on your personal key won’t stop you from finishing a lab.

Can I use Claude Code, Copilot, or Cursor instead?

For your capstone, yes: use whatever agent you prefer. The labs are written for OpenCode, so following along is easiest with it, but the concepts (plan/build modes, context files, the writer/reviewer pattern, MCP) transfer directly to other agents.

What data may I send to the model?

• Course lab data: yes. The lab dataset is synthetic and safe to share with the model.
• Your own unpublished research data: only if you have checked your own data-protection constraints first (funding terms, ethics approvals, personal or sensitive data). We cover this in Lecture 06. When in doubt, use a synthetic sample instead of real data.

How does the chatbot work?

The Oshu assistant embedded on this site answers questions from the course content. It runs on custom code hosted on Hetzner in Germany and generates its answers through the EU API of Mistral. Your messages are not used to train AI models. See the Privacy Policy for the full details.

Do I need to know Python?

Basic scripting experience in any language is enough. The labs use Python, but every step is guided, so you will not be left to write Python from a blank page. The course is about working with an agent, not about Python syntax.

What do I have to deliver?

A final presentation on Day 3. It covers a working demo of your project, a reflection on how you used AI tools, the challenges you hit, and your practical recommendations. Details and timing are on the Presentations page.