Sourcing Data for Analytics

3 credits · Engineering Professional

Course introduces students to the technical and non-technical aspects of collecting, cleaning and preparing data for use in machine learning applications. Technical aspects covered will include the types of data, methods of sourcing data via the web, APIs and from domain-specific sensors and hardware, an increasingly common source of analytics data in technical industries. The course also introduces methods and tools for evaluating the quality of data, performing basic exploratory data analysis, and pre-processing data for use in analytics. Non-technical aspects covered include an introduction to data privacy, GDPR, regulatory issues, bias and industry-specific concerns regarding data usage.