Machine Learning
Graduate-level ML: supervised vs unsupervised learning, training, and generalization.
Dr. Sofia Greco
ML Researcher
Supervised vs Unsupervised
Two ways a model learns from data.
Overfitting & Train/Test Splits
Measuring true generalization.
Gradient Descent
How models learn by following the slope downhill.
Neural Networks
Layers of neurons that learn features.
Common questions
Who is "Machine Learning" for?
It is written for learners at Master's level (Graduate), and for anyone older who wants a clear refresher on computer science. Graduate-level ML: supervised vs unsupervised learning, training, and generalization. There is no application or entry test — you can start the first lesson straight away.
How long does the course take?
There are 4 lessons totalling 38 minutes of reading and quizzes, laid out over 2 units. You can move at your own pace — progress is saved as you go.
What do I need to know before starting?
No prior coursework is assumed. The course opens with "Learning Paradigms", covering supervised and unsupervised, so the foundations are built in rather than expected.
Is the course free?
Yes. Every course on Monster Class is completely free, with no credit card, trial period or paywall. Creating a free account simply saves your progress, XP and place on the leaderboard across devices.