Artificial Intelligence for Project Managers

Understand AI well enough to make your own decisions about it.

Every project manager has now been told that AI is going to change the job. Far fewer could explain what a large language model is actually doing when it answers, why a model trained on poor data produces confident nonsense, or what to say when someone on your team wants to paste client information into a public chatbot.

This course closes that gap, and then puts the result to work.

What this course is

It is a foundational course in artificial intelligence, built for project managers and taught by one. It assumes you manage projects. It assumes nothing at all about your AI knowledge.

The focus is transferable AI literacy, responsible use, data, and practical generative AI and prompting for project work, rather than step-by-step training in the AI features of any particular project management application. Those features change every few months. What you learn here will still be useful when they do, and it will let you evaluate them yourself rather than taking a vendor's word for it.

Let me be clear about the shape of it, because that matters more than any feature list. The first half builds your understanding of the technology itself. The middle section is hands-on. The final section is six full interviews with practitioners doing this work now.

What you will study

The AI project management revolution. Why this moment is different from the last several things that were going to change project management, and what AI literacy actually means for someone in your role.

AI fundamentals. Machine learning, natural language processing, large language models and generative AI, each explained from the ground up and aimed at a project manager rather than an engineer. This is the part that makes everything else make sense, and it is why the course does not open with prompts.

Ethics, integrity and transparency. Leading projects where AI is in scope, and what responsible use looks like when you are the one accountable for the outcome.

Data. Data quality as the foundation everything else sits on, where bias enters a model and how to spot it, and the data literacy a project manager needs in order to ask the right questions of the people building these systems.

Generative AI and prompting. The hands-on section, described below.

Roles and teams in AI-enabled project management. As AI takes on more of the administrative work, the role changes shape. This section is about what remains, which is leadership, stakeholder relationships, team development, and the judgment calls that need a human in the chair.

Expert perspectives. Six interviews from The Project Management Podcast.

The hands-on section

Two lessons here are where the concepts become something you can use on Monday.

The first teaches prompt engineering properly: a formula you can apply immediately, the components that make a prompt work, how to turn a weak prompt into a strong one, and a downloadable library of prompt components to keep beside you.

The second is a live demonstration. You watch me work inside ChatGPT and Gemini on real project tasks, generating a work breakdown structure, running a risk analysis and mitigation plan, putting a Monte Carlo question to the model, and defining project success criteria. You will see how to control the format of what comes back, how to run a sequence of prompts rather than a single request, and a technique for having two different AI models critique each other's output so you are not relying on one of them to mark its own homework.

There is also a plain warning about company data policy, because the fastest way to get AI banned at your organisation is for a project manager to paste something into a chatbot that should never have left the building.

Six expert interviews

The final section is nearly six hours of conversation from The Project Management Podcast with people applying AI to real projects: what has worked, what has not, where the promises are running ahead of the practice, and what data literacy looks like in an AI-driven organisation.

These are full-length interviews rather than clips. Students have specifically called out these interviews as the part that took the concepts into real life. They are kept together at the end so you can work through them in one stretch, or return to them later, or pick the one that matches the problem in front of you.

Your PDUs and your certificate

The course carries 14.50 PDUs of formal education towards maintaining your PMI certification.

Udemy issues your Certificate of Completion once you have finished every lecture. It shows your name, the course title, the date, and the hours.

Who is teaching you

I am Cornelius Fichtner, PMP. I have been a project manager since 1989, and I have spent nearly twenty years teaching project managers, with more than sixty thousand students over that time.

Since 2005 I have hosted The Project Management Podcast, where I have recorded more than five hundred interviews with project managers, authors and practitioners around the world. That matters here more than it usually would. For the past two years I have been asking people on the podcast what AI is genuinely doing on their projects rather than what the vendors say it will do, and six of those conversations are in this course.

Before you start

No prior AI knowledge is needed. Everything is explained from the beginning, and every term is defined when it first appears.

Some real project management experience helps, because every concept here is framed against work you already do.

And one honest expectation. This is a long course and the first half is conceptual by design. If you want something you can apply this afternoon, you can jump ahead to the prompting lessons and come back for the rest. If you want to actually understand what you are working with, take it in order.