28-day beginner course

Introduction to AI

A plain-English guide to what AI is, how chatbots work, which tools matter, how to prompt well, what happens behind the scenes, and how to use AI responsibly.

28 days4 weeksGoal - Learn - Example - Practice - Checkpoint
Week 1

Foundations

Start with the core terms and mental models.

Day 1

What AI Is

GoalUnderstand AI as software that learns patterns from data and uses those patterns to help with tasks.

OpenStart Day 1 lesson.
Day 2

Machine Learning vs Generative AI

GoalSeparate traditional machine learning from generative systems like chatbots and image models.

OpenStart Day 2 lesson.
Day 3

Models, Apps, and Providers

GoalUnderstand the difference between an AI model, a chatbot app, and the company providing it.

OpenStart Day 3 lesson.
Day 4

Tokens and Context Windows

GoalLearn what text models actually read and why long conversations can lose details.

OpenStart Day 4 lesson.
Day 5

Prompts as Instructions

GoalUse prompts as clear instructions, not vague wishes.

OpenStart Day 5 lesson.
Day 6

Hallucinations and Verification

GoalUnderstand why AI can sound confident while being wrong.

OpenStart Day 6 lesson.
Day 7

Week 1 Review

GoalBuild a clean mental model of AI before using it heavily.

OpenStart Day 7 lesson.
Week 2

Everyday Use

Apply the tools to practical work.

Day 8

ChatGPT, Claude, Gemini, Copilot, and Others

GoalCompare major chatbot assistants by workflow instead of brand loyalty.

OpenStart Day 8 lesson.
Day 9

Writing with AI

GoalUse AI for drafts, structure, editing, tone, and feedback.

OpenStart Day 9 lesson.
Day 10

Research with AI

GoalUnderstand the difference between chat answers and source-backed research.

OpenStart Day 10 lesson.
Day 11

Files, PDFs, Images, and Audio

GoalUse multimodal AI to work with more than plain text.

OpenStart Day 11 lesson.
Day 12

AI for Coding and Data

GoalUse AI as a coding assistant, not an unsupervised engineer.

OpenStart Day 12 lesson.
Day 13

Privacy and Sensitive Data

GoalProtect personal, business, and confidential information.

OpenStart Day 13 lesson.
Day 14

Week 2 Review

GoalCreate a practical AI toolkit for daily work.

OpenStart Day 14 lesson.
Week 3

Behind the Scenes

Understand the systems under the interface.

Day 15

How Large Language Models Work

GoalLearn the basic behind-the-scenes idea of LLMs.

OpenStart Day 15 lesson.
Day 16

Training, Fine-Tuning, and Alignment

GoalUnderstand the stages that shape model behavior.

OpenStart Day 16 lesson.
Day 17

Embeddings and Semantic Search

GoalLearn how AI can search by meaning, not just keywords.

OpenStart Day 17 lesson.
Day 18

RAG: Retrieval-Augmented Generation

GoalUnderstand how chatbots answer from documents.

OpenStart Day 18 lesson.
Day 19

Agents and Tool Use

GoalUnderstand the difference between a chatbot and an AI agent.

OpenStart Day 19 lesson.
Day 20

Multimodal and Generative Media

GoalLearn how AI handles images, audio, and video.

OpenStart Day 20 lesson.
Day 21

Week 3 Review

GoalConnect AI outputs to the systems behind them.

OpenStart Day 21 lesson.
Week 4

Responsible Power

Use the tools with judgment and clear limits.

Day 22

Bias, Safety, and Limitations

GoalUnderstand why AI systems can be unfair, unsafe, or overconfident.

OpenStart Day 22 lesson.
Day 23

AI at Work and School

GoalUse AI ethically in learning and professional settings.

OpenStart Day 23 lesson.
Day 24

Automation Workflows

GoalTurn repeated tasks into reliable AI-assisted processes.

OpenStart Day 24 lesson.
Day 25

Evaluating AI Output

GoalLearn practical ways to judge quality.

OpenStart Day 25 lesson.
Day 26

Building an AI Learning Habit

GoalStay current without drowning in hype.

OpenStart Day 26 lesson.
Day 27

Choosing the Right AI Tool

GoalMake practical tool decisions.

OpenStart Day 27 lesson.
Day 28

Final Project: AI User Playbook

GoalFinish with a reusable public AI playbook.

OpenStart Day 28 lesson.

Glossary

AI
Software that uses learned patterns to help classify, predict, generate, search, or act.
Model
The trained engine behind an AI tool. The app is the interface around it.
Prompt
The instruction, context, and requested output you give the AI.
Token
A small chunk of text that language models read and generate.
Context window
The amount of text, files, and conversation the model can consider at once.
RAG
Retrieval-augmented generation: search first, then answer from the retrieved material.
Agent
An AI workflow that can plan steps and use tools, not only write a reply.
Hallucination
A confident-sounding answer that is unsupported, wrong, or invented.
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