ITI 350 Data Analytics
The course covers the breadth of activities and methods and tools that data scientists use to visualize and study patterns in data. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with lab sessions using a programming language. Important machine learning techniques are covered: regression, clustering, classification, association rules, time series analysis, and text analysis. The students are expected to create a final project related to their field of study, write a paper, and present it to the class.