AI Fundamentals Explained — ML, Deep Learning & Generative AI

AI Fundamentals: ML, Deep Learning & Generative AI

1 min readPublished 22 Jul 2026

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Artificial Intelligence (AI) is software that performs tasks that usually need human intelligence. It helps to see how the key terms nest inside each other.

Interactive explainer

The AI Landscape

How AI, ML, deep learning and generative AI nest together.

Tap or hover a part to learn more.

Artificial Intelligence

The broad field.

The widest circle: any software that performs tasks usually needing human intelligence — reasoning, perception, language. Everything below is a subset of AI.

Check your understanding

1. How do AI and machine learning relate?

2. What does generative AI do?

Keep learning

AI Fundamentals Large Language Models Microsoft AI-900

Practise this in AI Interview™

The landscape

AI — the broad field of intelligent systems.
Machine Learning (ML) — systems that learn patterns from data rather than being explicitly programmed.
Deep Learning — ML using multi-layer neural networks, powering modern breakthroughs.
Generative AI — models that create new content (text, images, code), e.g. LLMs.

AI learns from training data, so quality and bias in that data matter enormously. AI is a powerful tool — not magic — with real strengths and real limits, a theme throughout this path.

Interview Intelligence

How this topic actually shows up in interviews — and how to demonstrate you understand it.

Why employers ask about this

Every organisation is adopting AI, so a clear grasp of the fundamentals is now a baseline skill.

Technical questions

Explain the relationship between AI, ML, deep learning and generative AI.+

They nest: AI is broadest, ML learns from data, deep learning uses neural networks, and generative AI creates new content.

Behavioural questions

Tell me about adopting a new technology at work.+

Show curiosity, understanding its strengths and limits, and applying it responsibly.

Real-world scenarios

“A stakeholder thinks AI is infallible.”+

Expected answer: Explain AI learns from data and has real limits (bias, errors), so it augments rather than replaces human judgement.

Practise in AI Interview™Rehearse these questions, scored.Plan with Career Coach™A personalised path to your goal.Evidence it in Career Passport™Prove this skill to employers.

Employability Intelligence

Where this knowledge takes you — the jobs, skills and certifications it feeds into.

Relevant roles

AI PractitionerData AnalystAutomation Engineer

Skills you're proving

AI conceptsML basicsGenerative AI

Recommended certifications

Microsoft AI-900 (AI Fundamentals)Microsoft AI-102AWS AI Practitioner

Career progression

AI & Automation Fundamentals → AI/automation roles.

What employers expect

That you can use AI tools effectively, understand their limits, and automate work responsibly.

Frequently asked questions

What is the difference between AI and machine learning?

AI is the broad field of intelligent systems; ML is a subset where systems learn patterns from data rather than explicit rules.

What is generative AI?

AI that creates new content — text, images or code — such as large language models.

Why does training data matter?

Models learn from data, so its quality, coverage and bias directly shape the model's behaviour and fairness.

Practise what you've learned

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Missiora helps you measure, improve and evidence the capabilities employers actually value — start with the tools best suited to this topic.

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Missiora

Missiora is an AI Employability Intelligence platform. Our resources are researched and reviewed by the Missiora team to help you measure, improve and prove your career readiness.