Courses

We offer the following courses constantly in NSYSU:

Foundations of Manifold Learning

Starting from PCA and MDS, we explain the mathematical ideas behind classical and modern dimension reduction embeddings including ISOMAP, LLE, LE, HLLE, DM, etc.

Python and Machine Learning Algorithms

The course introduces various machine learning algorithms and focuses on how to write these algorithms from scratch.


Algebraic Graph Theory

In the course we will investigate the beautiful relations between matrices and graphs. Possible topics include, but not limited to, adjacency matrix and random walk, Laplacian matrix and graph partition, König graph and Cayley–Hamilton theorem.

Topological Methods in Graph Theory

Data Visualization

Other Courses given by our colleagues

Statistical Learning and Data Mining

Data Science Capstone Project