Good balance between the practical application of linear algebra as well as gentle introduction to some of the theoretical concepts.

Linear algebra topics selected for the application to data science. LU decomposition, PCA, SVD, and very little bit of Deep Learning / Neural Network. The content involves not just the arithmetics but also the understanding of the concepts and proofs.

Very caring and friendly professor.

For the students without the background of theoretical linear algebra (MAS 4105), which is myself, would struggle with the proof parts