IS 311 - Introduction to Data Science (3 Credits)

Prerequisite: IS 200 (or BUS 325 and CIS 101 ), MATH 315 , IS 211 , IS 362
The ability to understand, analyze, and interpret large and disparate data sets is increasingly important for gaining competitive advantage in the marketplace, and improving social conditions. This course uses the statistical and mathematical techniques that form the basis of descriptive and predictive analytics to extract qualitative insights from a variety of data types (e.g., customer preferences, purchasing and pricing, social network interactions, text, images, and mobile and ubiquitous outputs). Using existing programming and data management skills students apply them to the areas of data acquisition and cleaning, data exploration and visualization, mathematical model development, and graphical report creation. Areas of application can include social analytics, search engine algorithms, recommender systems, market analysis and demand estimation, customer segmentation and product pricing, healthcare, and transportation. In addition, students use current statistical analysis tools such as R., Case studies are used throughout the course.