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Artificial Intelligence (AI) Education for Teachers

Generative AI is transforming education — but before you can harness it effectively, you need to understand the foundations it's built on.

Artificial Intelligence (AI) Education for Teachers is a beginner-level online course from Coursera in Artificial Intelligence. It is structured in 6 modules with 4 stated learning outcomes, over 20h 1m. Learners rate it 4.7/5 from 967 ratings on Coursera.

Part of our Artificial Intelligence courses collection, where we compare it against 32 other courses.

★★★★★4.7(967 reviews) English

Course highlights

Provider Coursera
Duration 20h 1m
Level Beginner
Mode Self-paced
Language English
Certificate Yes — shareable certificate
Rating 4.7★ (967 reviews)
Price Check price

About this course

This Artificial Intelligence (AI) Education for Teachers course explores the foundations of AI, focusing on how generative AI is transforming education. It covers the history of AI since the 1950s, its broad applications across industries, and the ethical considerations involved in its development. You learn about fairness, transparency, privacy, and compliance in AI systems.

The course helps you develop key thinking skills for working with AI. This includes creative, critical, design, data fluency, and computational thinking. It teaches you how to apply these skills to solve problems where AI can be part of the solution. The program is self-paced, allowing you to complete modules and topics in any order that suits your learning style.

Upon finishing this AI course for teachers, you can compare AI with human intelligence and understand its evolution. You will identify various industry applications of AI. You will also explain the principles of ethical AI development and describe how existing thinking skills in curricula can be used to approach problems with AI solutions.

This course is designed for educators who want to understand AI's impact on teaching and learning, assuming you already know how to design and implement learning sequences for students. It does not require prior knowledge of coding or programming. If you are looking for a broader introduction to general AI concepts, consider Introduction to Artificial Intelligence (AI) from Coursera. For free introductory options, Introduction To Artificial Intelligence on Udemy offers a starting point.

What you’ll learn

Compare AI with human intelligence, broadly understand how it has evolved since the 1950s, and identify industry applications
Use creative, critical, design, data fluency, and computational thinking for AI
Explain ethical AI development: fairness, transparency, privacy, compliance
Describe how thinking skills embedded in curricula can be used to solve problems where AI has the potential to be part of the solution

Level and time commitment

Coursera lists this course at Beginner level.
No prior experience in the subject is assumed — this is where the provider expects a newcomer to start.
Time commitment: 20h 1m.
It is self-paced, so that figure is the material, not a fixed schedule.

Skills you’ll gain

Artificial Intelligence and Machine Learning (AI/ML)Analytical SkillsData EthicsEducation and TrainingInstructional DesignAI IntegrationsCritical ThinkingMachine LearningInstructional StrategiesTeachingAI literacyHuman Learning

What this course covers

6 modules

The 6-part outline Coursera publishes for this course, across 20h 1m.

Module 1 · Welcome to AI Education for Teachers
Module 2 · AI Fundamentals: History and Applications
Module 3 · Design and Critical Thinking for AI
Module 4 · Data Fluency and Computational Thinking
Module 5 · Ethical AI and Bias Awareness
Module 6 · Course Summary and Teaching Applications

What learners rate it

4.7
★★★★★
967 ratings

Rated 4.7/5 by 967 learners on Coursera (checked 10 Aug 2026).

This rating is collected by Coursera from its own enrolled learners. We reproduce it as reported and do not accept paid or incentivised reviews. See it on Coursera →

How this page is put together

Compiled by the CoursesGlobal editorial desk. Fees, ratings, duration and certificate details for the 1 course shown are read directly from Coursera course pages — we never estimate a price or a rating. Last verified 10 August 2026.

How we compare and rank courses · Our review policy · Affiliate disclosure

Compare with alternatives

Same topic, different trade-offs — here's who runs each one and what it's best at.

Course Provider Rating Price Duration Why pick this one
Artificial Intelligence (AI) Education for Teachers This Coursera 4.7★ Check price 20h 1m Most popular — 0 learners
YUVA AI for ALL Coursera 4.8★ Check price 8h 35m Highest rated (4.8★ from 433 reviews)
Introduction to Artificial Intelligence (AI) Coursera 4.7★ Check price 13h 25m Beginner-friendly · 13h 25m
Innovations in Investment Technology: Artificial Intelligence Coursera 4.7★ Check price 10h 25m Beginner-friendly · 10h 25m
See all Artificial Intelligence courses →

Common questions

How much does Artificial Intelligence (AI) Education for Teachers cost?

Coursera does not publish a price we can read on the course page, so we do not show one. Check the fee on the provider site — we would rather say nothing than quote a number we did not collect.

Does Artificial Intelligence (AI) Education for Teachers come with a certificate?

Yes — Coursera lists a certificate on completion. It is a course certificate, not a formal qualification or university credit.

How long does Artificial Intelligence (AI) Education for Teachers take?

Coursera lists it at 20h 1m. It is self-paced, so that is the volume of material rather than a deadline — how long it actually takes depends on the hours you put in each week.

Is Artificial Intelligence (AI) Education for Teachers suitable for beginners?

Yes. Coursera lists it at Beginner level, so no prior experience in the subject is assumed.

What does Artificial Intelligence (AI) Education for Teachers cover?

It is organised into 6 modules, starting with Welcome to AI Education for Teachers and going on to AI Fundamentals: History and Applications, Design and Critical Thinking for AI, Data Fluency and Computational Thinking, Ethical AI and Bias Awareness, among others. The full outline is on this page.