Course Description
Learn about preparation of informative, manageable datasets; accessing "big data" quickly and reliably during and subsequent to analysis; data pre-processing, analytics methods selection and testing, work flow design, and bulk data processing; exploratory data analysis including interpretation, generation of hypotheses and intuition about the data; prediction, utilizing statistical tools such as regression, classification, and clustering; communication of results through visualization, stories, and interpretable summaries.
Who should enroll: Students with prior experience/coursework in data analytics or statistics, students with experience in domains where big data techniques are employed, and students interested in graphical and written communication are all encouraged to join the class. You will work together in teams to develop significant analytics projects as a major part of this course.
Course Goals
Who should enroll: Students with prior experience/coursework in data analytics or statistics, students with experience in domains where big data techniques are employed, and students interested in graphical and written communication are all encouraged to join the class. You will work together in teams to develop significant analytics projects as a major part of this course.