This course gives an overview of fundamental topics in data science. Topics include: history and
recent advances in data science, overview of data manipulation, data
exploration, introduction to data mining and model evaluation. The first
half of the course focuses on analyzing real datasets and the second
half on various techniques for prediction tasks. This course will allow
students to have a hand-on experience on different datasets using the
Weka software package for data analysis.
Introduction to data science, overview of data
manipulation, data exploration, introduction to data mining, model evaluation, case
studies in data science
This course focuses on modelling most prevalent types of data: continuous, time series and categorical data. The emphasis is put on mathematical formulation, statistical decision making and implementations in python programming language. The topics include: basic linear algebra, principal component analysis, simple and multivariate linear regressions, time series analysis and models, logistic regresion and linear discriminant analysis. Each week consists of one in-class lecture and one programming lab.