Planning a Machine Learning Project
AWS Skill Builder
Last updated October 8, 2026
Planning a Machine Learning Project is a free, 30-minute course about a decision that comes before any model is built: is machine learning even the right tool for this problem? It is aimed at decision-makers and stays conceptual throughout. The course works through the questions worth asking up front — whether a machine learning (ML) solution fits the problem at hand, whether the data you have is ready for machine learning, how ML will affect a project's timeline, and what to ask early about getting a model into production. The thread running through it is requirements: the data, time, and production conditions a project needs to have a real chance of succeeding, so you can spot the mismatches before they become sunk costs.
What you'll learn
- Judging whether ML suits a given business problem
- Assessing whether your data is ready
- How ML affects a project's timeline
- Early questions about deploying a model to production
- The data, time, and production requirements behind a successful ML project
Frequently asked questions about Planning a Machine Learning Project
Who is Planning a Machine Learning Project for?
Nontechnical business leaders and decision-makers who need to judge, before committing resources, whether machine learning is the right approach and whether their data and timeline can support it.
Is Planning a Machine Learning Project free?
Yes — Planning a Machine Learning Project is completely free to take.
What are the prerequisites for Planning a Machine Learning Project?
AWS recommends taking an introductory machine learning course first.
Why we suggest this course
It covers the questions to settle before starting a machine learning project — fit, data readiness, timeline, and deployment — for the person deciding whether to approve one. Its value is in helping you say "not this one" early, rather than discovering it late. One thing to know: AWS recommends taking an introductory ML course first.