InternshipTools and first-week setup
The tools a Generative AI & Prompt Engineering intern uses and how to set up your workspace in week one.
These are the main tools for Generative AI & Prompt Engineering tasks. You do not need all of them on day one; the Level 1 tasks tell you when to install each one.
- ChatGPT / Claude / Gemini
- Python
- OpenAI or Anthropic API
- Prompt evaluation
Set up your workspace
- Create a free GitHub account if you do not have one, with a professional username, and set up your LinkedIn profile: every task is submitted with a LinkedIn post.
- Create one repository for the internship, for example generative-ai-and-prompt-engineering-internship, with a README that says who you are and what the repo holds.
- Keep one folder per task, named with the task number and title, so mentors find your work quickly.
- Commit small changes every day with clear messages. Your daily work report uses these commits as proof.
- Never commit passwords, API keys or personal data. Put secrets in a .env file and add it to .gitignore.
Your first tasks
| Task | What to do |
|---|---|
| Compare three AI assistants | Ask the same 5 questions (coding, maths, summary, translation, a fact) to three free AI assistants. Record answers in a table and note which was right, wrong or vague. |
| Write a prompt-engineering cheat sheet | Document role, task, context, format and constraints with one before/after example each. Commit it as README.md in a repo named genai-internship. |
| Zero-shot vs few-shot prompting | Classify 20 product reviews as positive/negative with a zero-shot prompt, then with 3 examples. Report accuracy for both and explain the difference. |
| Structured output with JSON | Write a prompt that turns 10 messy job postings into JSON (title, company, skills[], salary). Validate the JSON with a short Python or JS script. |