Artificial Intelligence (AI) · Intermediate level

Intermediate level · Module 2 of 6 · 16 guided hours

Working with AI Model APIs

Call large language model APIs from Python, control their behaviour, get structured outputs and manage cost.

Learning objectives

  • Send messages to language model APIs and handle responses
  • Request structured outputs and validate them
  • Estimate and control cost, latency and rate limits

Topics

  • chat message format and roles
  • model parameters
  • structured (JSON) outputs
  • validation
  • tokens, cost and latency
  • provider choice and data policies

Lessons

  1. Lesson 1 Calling a Language Model API

    Send a conversation to a language model API and read its reply.

    system messageuser and assistant messagesmodel parameterstoken usage

  2. Lesson 2 Structured Outputs

    Get machine-readable JSON from models and validate it before using it.

    JSON schemastructured outputvalidationfallbacks

  3. Lesson 3 Cost, Latency and Provider Choice

    Estimate and control the cost and speed of AI applications, and choose providers responsibly.

    token pricinglatencycaching and batchingdata policies and location

Practical activity

Build a script that turns free-text feedback messages into structured records (topic, urgency, location) with a language model API, validating every result and logging the cost.

Expected outcomes

  • Working model API integrations
  • Reliable structured outputs within budget

Assessment

Practical marked on correct API use, output validation and cost reporting.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.