Introduction to Machine Learning: Art of the Possible
AWS Skill Builder
Last updated September 12, 2025
Introduction to Machine Learning: Art of the Possible is a free, 30-minute primer that explains what machine learning is in plain language, with no coding involved. It is built for people who have to make decisions about ML without necessarily building it themselves, and it stays at the level of ideas throughout. The course works through three questions in turn: how machine learning can help, how it actually works, and — importantly — where it runs into trouble. That last part matters: rather than selling ML as a cure-all, the course is upfront that it has failure modes and limits you need to weigh before committing. A short closing section points to a few AWS services that put these ideas to work. The material is delivered as presentations, videos, and knowledge checks.
What you'll learn
- How ML can help solve real business problems
- How ML works, conceptually
- Where ML struggles — its failure modes and limits
- Weighing the benefits and risks of adopting ML
- Where a few AWS services apply ML in practice
Frequently asked questions about Introduction to Machine Learning
Who is Introduction to Machine Learning for?
Nontechnical business leaders and decision-makers involved in ML projects — and any curious beginner — who want a clear, jargon-light grounding in what machine learning can and can't do.
Is Introduction to Machine Learning free?
Yes — Introduction to Machine Learning is completely free to take.
What are the prerequisites for Introduction to Machine Learning?
None required; some basic computer knowledge and a rough sense of what machine learning is will help.
Why we suggest this course
A fast, plain-language orientation for business decision-makers and curious newcomers who want a realistic picture of what machine learning can do — and where it falls short — before investing in it. The honest treatment of ML's potential problems is the part that sets it apart from a sales pitch. One thing to know: it is built by AWS, so the closing section names a few of Amazon's own services (Forecast, SageMaker, Fraud Detector); the core ideas, though, are general and not tied to any platform.