AI Literacy Courses for Teachers: What I Learned and Where I Would Start

AI literacy is becoming part of a teacher’s professional knowledge.

At its simplest, it means understanding enough about how AI works to use and evaluate it critically, safely and responsibly. For teachers, that also means helping students recognise its strengths and limitations.

We do not need to become technical experts. We do need enough understanding to question AI-generated information, recognise possible bias, protect data and decide when AI is useful.

That distinction matters.

Being able to generate a worksheet quickly is a useful skill. Being able to decide whether that worksheet is accurate, appropriately challenging and genuinely helpful to a particular class is a professional one.

AI in education can feel like a noisy space. New tools appear constantly. Some people talk as though AI will transform every part of teaching; others would prefer it stayed out of the classroom altogether. My own starting point was somewhere in the middle: curious, but cautious. I did not want to use AI simply because it was new, nor did I want to dismiss it before I understood it properly. So I began learning.

Over time, I completed five courses from AI for Education, the Chartered College of Teaching, the ADAPT Centre, Google and UNESCO. There was some overlap, but each approached AI literacy from a different angle.

Some were practical. Some made me think more carefully about safeguarding and professional responsibility. Others explored how AI systems are created, whose interests they may reflect and what their growing use could mean for education more widely.

This is not a league table. I am writing as a classroom teacher who wanted enough knowledge to make sensible, informed decisions about AI.

A short evaluation of each course:

1. AI for Education: a practical introduction

An Essential Guide to AI for Educators is a free, self-paced course designed to help educators get started with ChatGPT. It covers prompting, classroom and administrative uses, ethical considerations and ways of introducing AI to students. This was the course that made AI feel immediately usable.

It did not assume teachers already understood the terminology, and the examples were based on familiar tasks such as planning, creating resources and adapting learning.

The section on prompting was particularly useful. “Create a quiz about protein” is very different from specifying the course, age group, learning outcomes, level of challenge, question style and misconceptions you want to address.

The course also considers how students might use AI. I liked that realistic approach. Students need help to question outputs, recognise limitations and use these tools without allowing AI to do all the thinking.

Best for: teachers who want a practical introduction to generative AI.

What stayed with me: a good prompt is not a magic formula. It is a clear explanation of the context and the outcome needed.

Limitation: its strength is practical use. Teachers looking for a deeper exploration of how AI works, data, ownership and wider ethical questions will need to look elsewhere.

2. Chartered College of Teaching: professional responsibility first

The Safe and Effective Use of AI in Education materials and certification focus much more closely on the responsibilities that come with using AI in schools.

I found the content on safeguarding, data protection, intellectual property and academic integrity particularly valuable. These areas can easily be overshadowed when the conversation focuses on what AI can create or how much time it might save. As teachers, however, we cannot separate convenience from professional responsibility.

The course also reinforces the need to question polished AI-generated outputs. A confident response can still contain factual errors, omit important context or reproduce bias. In education, “nearly right” is not always good enough.

For me, this course provided an important foundation. It did not suggest that teachers should avoid AI, but it made clear that its use needs boundaries, oversight and professional judgement. Teachers in Northern Ireland will still need to follow the guidance and policies relevant to their own school and educational context.

Best for: teachers and school leaders who want to understand safe and responsible AI use.

What stayed with me: responsible use is not something to bolt on afterwards. It needs to be built in from the start.

Limitation: it is less focused on creative experimentation, so teachers wanting practical experience may want to pair it with a more hands-on course.

3. ADAPT Centre: understanding AI more critically

The ADAPT Centre’s AI Literacy in the Classroom course is a short, self-led programme for post-primary teachers covering AI literacy and AI ethics.

This course widened my understanding of what sits behind the tools. It explores big data, how models are trained, questions of ownership and the political and social influences embedded in technology. That matters because AI systems are not neutral collections of facts. Decisions are made about the data included, the outcomes prioritised and the voices that are better, or less well, represented. Critical AI use therefore involves asking more than, “Is this answer correct?” We also need to ask, “Why might the system have produced this answer, and what could be missing?”

This course felt accessible without oversimplifying the issues.

Best for: post-primary teachers who want to understand AI critically and help students do the same.

What stayed with me: AI literacy is about more than using tools. It is also about data, influence, ownership and whose knowledge is represented.

Limitation: at around 90 minutes, it provides a framework for thinking rather than an extensive bank of classroom strategies.

4. Google: hands-on practice with Gemini and NotebookLM

Google’s free Generative AI for Educators with Gemini course gives teachers practical experience with tools such as Gemini and NotebookLM. What I valued most was the opportunity to move from reading about AI to actually testing it.

The course reinforced how much context matters. Subject, age group, intended learning, format and constraints all affect the usefulness of an AI response.

NotebookLM was particularly interesting because it allows users to work from a chosen collection of sources. For a teacher, that can be useful when exploring a specification, guidance document or set of notes. It does not remove the need to check the output, but it gives the work a more defined starting point than a completely open request.

This is, of course, a Google course built around Google tools. The wider skills are transferable, but teachers working mainly with Microsoft 365 and Copilot may apply them using different platforms.

Best for: teachers who want guided, hands-on experience, particularly with Gemini or NotebookLM.

What stayed with me: AI becomes more useful when it has good source material and a clearly defined educational purpose.

Limitation: it is understandably product-focused, so I would see it as practical training rather than a complete introduction to AI literacy.

5. UNESCO: stepping back to see the bigger picture

UNESCO’s work on Artificial Intelligence and the Futures of Learning took me beyond individual tools and classroom tasks.

Its human-centred perspective places AI within wider questions about inclusion, equity, ethics, access and the future role of education. This was less about creating tomorrow’s lesson resource and more about asking what kind of education we want AI to support.

Who benefits from these technologies? Who may be excluded? Which languages, cultures and forms of knowledge are strongly represented, and which are not? How do we use AI without weakening human agency or the relationships at the heart of teaching?

I found that broader perspective valuable. It is easy to become absorbed in what a tool can produce and forget to ask what its use may change.

Best for: teachers who want to consider AI within a wider ethical and human-centred context.

What stayed with me: the important question is not simply what AI can do, but what we want education to remain and become as AI develops.

Limitation: it is the least likely of the five to give you something to try in tomorrow’s lesson. Its value lies in the questions it makes you ask.

So, where would I start?

I would not suggest that every teacher needs to complete all five. There is overlap between them, and each offers something slightly different. It makes more sense to choose one or two depending on what you want from the training.

For a teacher completely new to generative AI, I would probably begin with AI for Education’s Essential Guide. It is approachable, practical and helps make the terminology and basic uses of generative AI feel manageable.

I would then choose a second course based on what I wanted to understand next:

• Chartered College of Teaching if you want to focus on safeguarding, data protection, intellectual property, academic integrity and professional responsibility.

• ADAPT Centre if you want to understand AI more critically and explore issues such as data, ownership, influence and bias.

• Google if you want hands-on experience with Gemini and NotebookLM.

• UNESCO if you want to step back from individual tools and think about human agency, equity and the wider future of education.

For teachers using AI in school, I would place the Chartered College of Teaching course particularly high on the list. Practical skills are useful, but understanding the professional responsibilities that sit behind their use is just as important. Choose the training that helps you answer the questions you actually have.

What the courses changed for me

Completing these courses did not make AI-generated resources suddenly reliable. I still need to check facts, adapt language, correct weak questions and make sure material matches the curriculum and the needs of my students.

If anything, the more I have learned about AI, the more conscious I have become of the repair and maintenance involved. A polished output may still need substantial teacher input. Subject knowledge, knowledge of the students and an understanding of how learning happens remain essential.

Instead of simply asking, “What can this tool make?”, I now ask:

• Will this improve learning, or merely produce more content?

• Is the information accurate and appropriate for this class?

• What thinking should remain with the student?

• What data am I sharing?

• Could I explain and justify this use to a parent, colleague or school leader?

• Is AI genuinely the best tool for this task?

For me, that is the real value of AI literacy. It is not about chasing every new tool or presenting AI as the answer to every educational problem. It is about knowing enough to explore its possibilities, recognise its limitations and make a professional judgement about when, and when not, to use it.

Course names, content and availability can change. The links and course information in this post were checked on 3rd September 2026. All views are based on my own experience of completing the courses.