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AI & Machine Learning
Machine Learning Foundations
Machine learning is not magic; it is optimization with data. Fit models by hand, watch gradient descent roll across a 3D loss surface, and see exactly when a model stops learning and starts memorizing.
What you’ll learn
- Frame business problems as supervised or unsupervised learning tasks
- Explain loss functions and why training minimizes them
- Describe how gradient descent trains a model, and choose a sensible learning rate
- Interpret classifiers, decision boundaries and predicted probabilities
- Detect overfitting and prevent it with validation data and regularization
Curriculum
Module 1 · Learning from data
5 lectures- 01What it means for a machine to learnInteractiveFree15 min
- 02Linear regression and the loss functionInteractiveFree18 min
- 03Gradient descent: finding the bottom of the valley3D modelFree19 min
- 04Classification and logistic regressionInteractiveFree19 min
- 05Overfitting and generalizationInteractiveFree18 min
Module 2 · Models that power industry
5 lectures- 06Decision trees and random forestsIncluded with the course
- 07Gradient boostingIncluded with the course
- 08Measuring models: precision, recall and ROCIncluded with the course
- 09Feature engineeringIncluded with the course
- 10Clustering with k-meansIncluded with the course
Module 3 · Beyond the basics
4 lectures- 11Dimensionality reduction with PCAIncluded with the course
- 12Anomaly detectionIncluded with the course
- 13Recommender systemsIncluded with the course
- 14Capstone: an end-to-end prediction serviceIncluded with the course
Who this course is for
- Engineers who work alongside data-science teams
- Analysts ready to move from dashboards to models
- Managers who need to judge ML proposals with confidence
Before you start
School-level algebra. Every formula is explained visually; no calculus background is required.
Keep going
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Training a team on this?
We can combine Machine Learning Foundations with other courses into a learning path built around your team’s roles and goals.