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.