The Data Science Institute for Summer 2017 took place in Room # N110 (Callaghan Auditorium), College of Public Health Building.
June 5, 2017 - 9 am - 12 pm: Introduction to Python Data Analytics - Dr. Kang Pyo Lee
This introductory course will cover the basic elements in Python data analytics. The topics to be covered in the morning sessions include a brief introduction to data science and data analytics framework/tools/libraries, data handling with Python, and data analysis and visualization with Python. In the afternoon hands-on sessions, the attendees will be able to experience what data scientists actually do with some interesting datasets using the Jupyter Notebook. No prior experience with Python is necessary for this course.
June 6, 2017 - 9 am - 12 pm: Introduction to R - Dr. Ariel Aloe
This introductory course in R will begin by covering the basic data and programming structures of the R language. According to interest and time available, subsequent topics will include linear algebra routines, data visualization, enhancing computational performance, and fundamental statistical procedures. Data analysis will be a fundamental part of the course.
June 7, 2017 - 9 am - 12 pm: Geovisualization and GeoVisual Analytics - Dr. Caglar Koylu
The course covers the topics of Geographic Information Science, Geovisualization, and Visual Analytics
June 8, 2017 - 9 am - 12 pm: - Social Media Analytics with Python Dr. Kang Pyo Lee
This unique course will introduce the basic elements in big data based social media analytics using Python. In the morning sessions, the attendees will learn how to view, utilize, analyze social media data in terms of finding answers to a research question. In the afternoon hands-on sessions, the attendees will be able to find an opportunity of collecting, processing, and analyzing real Twitter data focusing on a specific target of interest. Prior experience with Python is recommended, but not required. Please note that social network analysis will not be covered significantly in this course, because it will be further covered by other course on Friday entitled "Network Analysis Using R".
June 9, 2107 - 9 am - 12 pm: Network Analysis Using R - Dr. Daniel Sewell
Introduction to Social Network Analysis with R will introduce attendees to concepts of social network analysis by illustration. The course will walk through R code, learning what the code does and introducing network concepts along the way. Attendees will leave with knowledge of commonly used R packages useful for network analysis. At least a small amount of prior experience with R is recommended.