Course Description
This course provides an introduction to data science and analytics which starts from the identification of data analytics problems to finding and implementing solutions to these problems. An introduction to the design of dimensional models and data warehouses is also included. Visualization techniques are also discussed. This course also gives an overview of the various data analytics models for classification, regression, time series, association, clustering, text mining and optimization problems.
Prerequisite Concepts: None
Course Outline:
I. Introduction to Data Science and Analytics
II. Case Study: Data Analytics Project Identification
III. Introduction to Descriptive Analytics
IV. Case Study: Data Analysis using R
V. Visualization
VI. Case Study: Graphics Design
VII. Introduction to Predictive Analytics: Classification
VIII. Case Study: Classification Analysis using R
IX. Introduction to Predictive Analytics: Regression and Time Series Analysis
X. Case Study: Regression Analysis
XI. Predictive Analytics: Modern Tools and Unsupervised Learning
XII. Case Study: Text Mining
XIII. Prescriptive Analytics
XIV. Case Study: Linear Programming