Course Code
Course Title
Data Science
Description
Students will be taken through the techniques for discovering insights from massive amounts of structured and unstructured data to help shape or meet specific needs and goals. The course will demonstrate data analytics to drive decision-making and lean on automation and machine learning as core components of Artificial Intelligence Topics included: Multivariate Data Analysis, OMICS Data and Bioinformatics Algorithms, Nonparametric Data Analysis, Financial Data Analysis, Data Compression and Modeling, Data and Visual Analytics, R for Data Science, Dimensionality reduction, Big Data Integration and Analytics, IoT Analytics, Data Mining Algorithms In R
Recommended Reading
- Ian H. Witten & Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2005
- Mohammed J. Zaki & Wagner Meria Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms
- Jeff Leek, The Elements of Data Analytic Style
- Mike Barlow, Real-Time Big Data Analytics: Emerging Architecture, 2013
- Scott Murray, Interactive Data Visualization for the Web, 2013