FoundationsBeginner

Software Engineering for AI Systems

Four weeks on the engineering practice AI work assumes but rarely teaches: version control that survives collaboration, APIs that fail well, containers, CI, and the observability you will need the first time something breaks in production.

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Duration: 4 weeks
Level: Beginner
Format: Live online
Investment: Request pricing
Next cohort: Dates announced soon

Who this is for

Able to write and run Python
Basic command line familiarity

This is not for

Senior engineers who already ship containerised services with CI

What you leave with

A containerised service with CI running tests on every push
An API with proper error contracts and structured logs
A runbook someone else could follow at 2am

Tools and stack

Git and GitHub ActionsFastAPIDockerpytestOpenTelemetry

Curriculum

Module 1 — Git as a team tool

Branch, review and merge without fear
Write commits someone can read later
Recover from the usual disasters

Module 2 — APIs that fail well

Design clear request and response contracts
Return errors a client can act on
Version an API without breaking callers

Module 3 — Containers and environments

Containerise a Python service
Keep images small
Manage secrets without committing them

Module 4 — CI and observability

Run tests automatically on every push
Emit structured logs and traces
Write a runbook for the failure you expect

How this program handles evaluation and governance

Auditability is an engineering property before it is a policy one. If your service has no structured logs, no CI and no runbook, no governance document will make its behaviour reconstructable. This course builds that substrate.