Course · Build
Building with AI APIs — practical LLM integration
Ship one real AI feature with OpenAI or Anthropic — tokens, prompts, costs, errors, case study.
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AI products · Shipping
Integrate · Deploy · Case study
01
What
02
Why
03
Outcome
What this course is
You integrate an LLM API (OpenAI or Anthropic) into one real feature: chatbot, summariser, code explainer, or similar. You handle token limits, prompt design, API cost awareness, and error handling. You deploy it and write a short case study — not a tutorial copy-paste.
Why it exists
Knowing AI theory from a semester course is different from putting AI inside a product. Employers and clients pay for people who can integrate models with care. This is the skill gap between “I used ChatGPT” and “I shipped an AI feature.”
What you do
- Connect OpenAI or Anthropic to a small product feature
- Handle tokens, prompts, costs, and API failures
- Deploy the feature for a demo or real users
- Write a portfolio case study of what you shipped
You leave with
A deployed AI-powered feature with a case study on your portfolio.
