Data Scientists extract knowledge and insights from structured and unstructured data. They draw
upon the practice of data analysis, using predictive analytics, data mining, text mining, pattern
recognition, data modeling, machine learning, and various statistical methods in order to solve
large scale problems and understand the meaning behind vast data sets.
Examine Data Science from a practitioner point of view and introduce topics from basic concepts and methodologies to advanced
Concentrate on data compilation, recommender systems, preparation and modeling, regression, time series analysis, multivariate
analysis, Bayesian methods, stochastic models, clustering, etc. that occur throughout the
life-cycle of data science.
Gain practical knowledge with open source tools and statistical packages (e.g., R, MATLAB, Python, SPSS).