Machine learning courses and concepts
Machine learning is the branch of AI in which a system learns to do a task by finding patterns in examples, rather than being programmed with a rule for every case. It is the layer almost everything else rests on — the models behind generative tools and agents are themselves machine-learned — and it remains a working field in its own right wherever the job is prediction, classification or ranking. Learning it turns out to be less about algorithms than about the discipline around them: what you trained on, and how you know the result is any good.
The vocabulary of machine learning
A striking share of these terms are units of measurement. Accuracy, precision and recall, and the various ways a set of predictions gets laid out for inspection — this is the language of judging whether a model is any good, and it is the part a course outline assumes you already have. It is also what lets you assess a number somebody else shows you: a model reported as accurate can still be useless, and this vocabulary is how you tell.
Courses on machine learning
The dividing question is whether your problem is framing the work or building the model. One group covers the decisions made before any model exists — whether machine learning is the right tool at all, what data would have to exist, what a good outcome would even look like; the other is the build itself, from preparing data through training to keeping a deployed model honest, and the two are rarely taught together.
Learn AI — the ideas, without building anything
Elements of AI: Introduction to AI
University of Helsinki & MinnaLearn
Exploring Artificial Intelligence Use Cases and Applications
AWS Skill Builder
Fundamentals of Generative AI
AWS Skill Builder
Fundamentals of Machine Learning and Artificial Intelligence
AWS Skill Builder
Introduction to Machine Learning: Art of the Possible
AWS Skill Builder
Machine Learning Terminology and Process
AWS Skill Builder
Planning a Machine Learning Project
AWS Skill Builder
Use AI — use trained models and services
Develop AI — build, train and run models
Advanced Machine Learning Operations
Databricks
Amazon SageMaker AI Getting Started
AWS Skill Builder
Create machine learning models
Microsoft Learn
Data Preparation for Machine Learning
Databricks
Design a machine learning solution
Microsoft Learn
Elements of AI: Building AI
University of Helsinki & MinnaLearn
Introduction to Amazon SageMaker Notebooks
AWS Skill Builder
Machine Learning at Scale
Databricks
Machine Learning Model Deployment
Databricks
Machine Learning Model Development
Databricks
Operationalize machine learning models (MLOps)
Microsoft Learn
Professional Machine Learning Engineer Certification
Google Skills
Train and manage a machine learning model with Azure Machine Learning
Microsoft Learn
Machine learning is the common ancestor of most of the rest of AI, so it tends to be a subject you return to rather than finish. Learn AI puts it in context alongside the newer things built on top of it; Use AI covers applying models and services without training anything yourself; Develop AI is the hands-on route — building, evaluating and running models as a job.
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