R E B O OT C O M PU T E R S E RVI C ES I N C . · C O L L E G E ST U DY S E R I ES
AI 101
The Complete Study Guide to Artificial Intelligence
Concepts · Machine Learning · Neural Nets · Ethics · Practice
Inside this guide
1 · What Is Artificial Intelligence?
2 · A Short History & the Big Ideas
3 · Machine Learning Fundamentals
4 · Neural Networks & Deep Learning
5 · Natural Language & Large Language Models
6 · How Models Are Trained & Evaluated
7 · AI Ethics, Bias & Safety
8 · Key Terms Quick Reference
9 · Practice Questions with Answers
10 · Glossary
A self-study companion for introductory AI · rebootcs.com
, 1 · What Is Artificial Intelligence?
Artificial Intelligence (AI) is the field of building computer systems that perform tasks normally requiring human
intelligence — perceiving, reasoning, learning, and deciding. It sits at the intersection of computer science, mathematics,
statistics, and cognitive science.
Narrow vs. General AI
Narrow (weak) AI is built for one task — spam filters, recommendation engines, chatbots. Every AI system in use today
is narrow. General AI (AGI) would match human flexibility across any task; it remains hypothetical. Superintelligence
would exceed human ability broadly — a topic of research and debate, not a current product.
How AI Relates to Its Subfields
Think of nested circles: AI is the broad goal; Machine Learning (ML) is the dominant approach — systems that learn
from data; Deep Learning is a subset of ML using large neural networks; and Generative AI (including today's large
language models) is a recent branch of deep learning that creates new text, images, and audio.
Key idea: Classic software follows rules a programmer writes. Machine learning instead discovers the rules from
examples.
© Reboot Computer Services Inc. · Created by Mario Washington · Page 2 of 12
AI 101
The Complete Study Guide to Artificial Intelligence
Concepts · Machine Learning · Neural Nets · Ethics · Practice
Inside this guide
1 · What Is Artificial Intelligence?
2 · A Short History & the Big Ideas
3 · Machine Learning Fundamentals
4 · Neural Networks & Deep Learning
5 · Natural Language & Large Language Models
6 · How Models Are Trained & Evaluated
7 · AI Ethics, Bias & Safety
8 · Key Terms Quick Reference
9 · Practice Questions with Answers
10 · Glossary
A self-study companion for introductory AI · rebootcs.com
, 1 · What Is Artificial Intelligence?
Artificial Intelligence (AI) is the field of building computer systems that perform tasks normally requiring human
intelligence — perceiving, reasoning, learning, and deciding. It sits at the intersection of computer science, mathematics,
statistics, and cognitive science.
Narrow vs. General AI
Narrow (weak) AI is built for one task — spam filters, recommendation engines, chatbots. Every AI system in use today
is narrow. General AI (AGI) would match human flexibility across any task; it remains hypothetical. Superintelligence
would exceed human ability broadly — a topic of research and debate, not a current product.
How AI Relates to Its Subfields
Think of nested circles: AI is the broad goal; Machine Learning (ML) is the dominant approach — systems that learn
from data; Deep Learning is a subset of ML using large neural networks; and Generative AI (including today's large
language models) is a recent branch of deep learning that creates new text, images, and audio.
Key idea: Classic software follows rules a programmer writes. Machine learning instead discovers the rules from
examples.
© Reboot Computer Services Inc. · Created by Mario Washington · Page 2 of 12
