Lesson 01 — The IT Map

A tour of what IT people work on — and why nobody can do all of it.

IT Landscape Module 1

Why you're here

This course is built for three audiences:

• Career switchers — you're thinking about moving into tech and want a map before the deep dive.
• Non-tech managers — you work next to engineers and want to follow the conversation.
• Motivated relatives of techies — you want to understand what they actually do all day.

Goal: leave this course knowing which area you'd want to learn more about.

IT is a city

Every business runs on the whole city. Most engineers live in one or two neighborhoods.

The 7 neighborhoods

1. Frontend — what the user clicks: web pages, mobile apps.
2. Backend & APIs — the brain behind the storefront.
3. Databases & Data — where state lives.
4. Networking & The Internet — how anything talks to anything else.
5. DevOps & Cloud — how code gets to real users, 24×7.
6. Security — keeps everyone else's mistakes off the front page.
7. AI / ML — the newest neighborhood, re-shaping the rest.

What "writing software" actually looks like

A typical engineer's day:

• Reading existing code
• Writing new code (a smaller share than you'd think)
• Reviewing teammates' code
• Fixing bugs
• Designing how things connect
• Meetings about all of the above

Not "typing furiously into a black screen."

The tool landscape

Names you'll meet in any modern team:

• GitHub — where the code lives.
• VS Code — the editor most people open.
• Slack — where the team talks.
• Jira — where the work is tracked.
• AWS Console — where the cloud bill lives.
• ChatGPT / Claude — the AI assistant in every workflow.
• Docker — the box code ships in.
• Terraform — infrastructure described as text.

Most IT workers see most of these every week.

Languages aren't religions

Python · JavaScript · Go · TypeScript · Rust · SQL

A tool, not a tribe. Most engineers use 2–4 languages daily and pick up new ones over a career.

What an "engineer" actually does

Roles you'll hear named

• Software Engineer — the generalist who ships features.
• DevOps / SRE — keeps the production system alive.
• Data Engineer — builds the pipelines that move data.
• Data Scientist — turns data into answers.
• ML Engineer — puts models into production.
• Security Engineer — keeps everyone honest.
• Product Manager — decides what gets built.
• UX Designer — decides how it feels to use.

Lesson 14 expands on every one of these.

The 2026 reality

• Every team uses cloud. Owning your own servers is now the exception.
• Every team has AI assistants in the loop. Code, docs, reviews, customer support — touched by an LLM.
• "Full-stack solo" is back. AI handles a lot of glue work, so one person can ship more on their own than five years ago.

How to read this course

• 12 lessons, ~45 min each.
• Slides = the talk.
• Theory = the read.
• Homework = the tool-tour.
• No code. The goal is vocabulary + a mental model, not job-readiness on day one.

Recap

• IT is many fields, not one.
• Engineers spend most of their time reading and designing — not typing.
• You don't need to learn it all to be useful.