Fundamentals of data science

This course will provide a comprehensive overview of the probability distributions and the statistical estimators. The derivations of Gaussian and Poisson distributions will be presented. Law of large numbers and central limit theorem will be proven. Maximum likelihood and maximum a priori will be introduced. The course will conclude by discussing how to apply those estimators to the real-world problem.

Class 1 - Class guidance (in preparation)

Class 2 - Fundamentals of data analysis

Class 3 - Classification and model evaluation

Class 4 - Clustering (in preparation)

Class 5 - Principal component analysis (in preparation)

Class 6 - Dimension reduction

Class 7 - Ensemble learning