The full lesson breakdown

Where AI already saves professionals hours every week — and where it doesn't.

A plain-language explanation of machine learning and language models — no math required.

GPT, Claude, Gemini and friends: what a "model" is, and how to choose one for a task.

The human-in-charge workflow: AI drafts and computes, you verify and decide.

Strengths, limits, and hallucinations — and how to work safely around them.

How to ask so you get useful answers: role, task, format, constraints.

Feeding documents, data, and background so the AI answers about your work.

Decomposing a big job into steps an AI can do reliably, one at a time.

Summarizing standards, comparing options, and checking sources without being misled.

Reports, emails, and data interpretation with AI as your first-draft engine.

How programs talk to each other — explained with everyday analogies.

The password that spends your money: what keys are, and why they must stay secret.

What the browser does, what the backend does, and why the difference matters for security.

Your first real API call: HTTP POST, JSON, and the OpenAI SDK in Python.

Reading the response, handling errors, and using the answer inside your program.

Environment variables, .env files, .gitignore, and what never goes in your code.

Cleaning, merging, and transforming spreadsheets with AI-generated scripts.

From raw results to a formatted report in your company template.

Building and verifying calculation sheets with AI assistance.

Extracting data from PDFs and scans into structured, usable form.

Drafting, summarizing, and templating routine correspondence.

Turning unstructured text into tables, JSON, and database rows.

Chaining AI with simple scripts so weekly chores run themselves.

Just enough Python to automate your work — written with an AI pair-programmer.

Calling AI and other services from your own scripts and tools.

Storing and querying your data so AI tools have something reliable to work with.

Wrapping your automation in a simple interface colleagues can use.

Linking AI to the software you already run — Excel, engineering tools, and more.

Build the exact chatbot running on this website: frontend, backend, and OpenAI.

Assistants that know your documents, procedures, and terminology.

Finding answers inside large document sets with AI-powered search.

Small, focused tools that solve one engineering task extremely well.

Connecting everything: triggers, AI steps, and outputs in one pipeline.