Re:Ask HN: Which MOOCs in Math/CS are worth still worth taki...
by minhmeoke on Tuesday August 30, 2022 @01:35AM
(#32646973)
I liked the EdX Statistical Learning course by Trevor Hastie and Robert Tibshirani, it's a great introduction to statistical modeling and data science (assuming you already have a solid math and statistics background):
https://www.edx.org/course/statistical-learning
It is not too math heavy, and the focus is on basic, interpretable approaches and concepts like:
- linear and polynomial regression
- logistic regression and linear discriminant analysis
- cross-validation and the bootstrap
- model selection and regularization methods (ridge and lasso)
- tree-based methods, random forests and boosting
- support-vector machines
- neural networks and deep learning
- survival models; multiple testing
- some unsupervised learning methods like principal components and clustering (k-means and hierarchical).
The instructors are really articulate and passionate about teaching well. As a bonus, there are guest speakers about every second week including Jerome Friedman and Geoff Hinton.
It is not too math heavy, and the focus is on basic, interpretable approaches and concepts like:
- linear and polynomial regression
- logistic regression and linear discriminant analysis
- cross-validation and the bootstrap
- model selection and regularization methods (ridge and lasso)
- tree-based methods, random forests and boosting
- support-vector machines
- neural networks and deep learning
- survival models; multiple testing
- some unsupervised learning methods like principal components and clustering (k-means and hierarchical).
The instructors are really articulate and passionate about teaching well. As a bonus, there are guest speakers about every second week including Jerome Friedman and Geoff Hinton.