ITS/ISRC Data Science Institute Scheduled for January 6-9, 2020

December 12, 2019

The University of Iowa, a pioneer in Informatics research, will offer its data science institute in January and June 2020. The institute will include a number of mini-classes in the morning to teach participants (faculty, graduate, and undergraduate students) the basic building blocks of coding as applied in the fields of the Biological, Physical, and Social Sciences. The January session will focus on basic introductions to the software while the June session will focus on more advanced applications using these software tools such as mixed models, social media analytics, and network analysis. Topics for January 2020 include the Python, R, and Stata programming and statistical analysis languages as well as a session on using High Performance Computing resources at Iowa. Faculty and staff from UI will teach the various short courses. Each course will involve a three and a half house morning session focused on instructor presentation of the material.

Visit our website for more information.

Follow the below link to register for the January Data Science Institute. There is no fee associated with the institute. You can register for all the sessions or individual sessions (see schedule below).The number of seats per session is limited to 50. There will be a waitlist accessed through the registration survey after the quota is filled for each session.

The Data Science Institute is organized and supported by ITS – Research Services and the Iowa Social Science Research Center, part of the UI Public Policy Center.

Please contact Fred Boehmke, Sai Ramadugu, or Elizabeth Menninga with questions.

Schedule

January 6, 2020 - 8:30 Am - 12:15 Pm: Introduction to Stata - Dr. Frederick J. Boehmke
This introductory course in Stata will cover the basics of data preparation and manipulation in Stata. Topics addressed will include importing data, merging and combining data sets, cleaning data, variables, variable manipulations, loops, and data visualization.

January 7, 2020 - 8:30 Am - 12:15 Pm:  Introduction to Tidyverse/R - Giang Rudderham
This hands on course will provide an introduction to the tidyverse, a data analysis framework in R that provides users a simple vocabulary to data analysis. Topics covered will include: introduction to data visualization, data management, and exploratory data analysis using the tidyverse. This course is intended to be hands on, therefore attendees are encouraged to bring a laptop with R and RStudio already installed. No prior R knowledge is needed.

January 8, 2020 - 8:30 Am - 12:15 Pm: Introduction to Python Data Analytics - Dr. Kang Pyo Lee
This introductory class will cover the basic elements in Python data analytics and provide hands-on practice. The topics to be covered include an introduction to data analytics and Python, Python basics for data analysis, and data preparation/exploration/visualization using widely used data analytics libraries in Python. Participants will also be able to learn how to take advantage of an interactive web-based data analytics environment called Jupyter Notebook. No prior experience in Python is necessary for this class. Participants will be expected to bring their own laptops.

January 9, 2020 - 8:30 Am - 12:15 Pm:  - Introduction to High Performance Computing (HPC) using Argon - Dr. Sai Kumar Ramadugu
This session is intended for anyone who will be running jobs on Argon.  The training session covers the following aspects:

  • How to make the most effective use of HPC resources
  • Connecting to the Argon cluster
  • Launching HPC jobs
  • Getting your data to and from Argon
  • Getting access to the software you need

For Introduction to HPC using Argon workshop, attendees need an account on the HPC cluster, Argon. If you do not have an account on Argon, you cannot do the hands-on session. Please apply HERE if you do not have an account.

Individuals with disabilities are encouraged to attend all University of Iowa-sponsored events. If you are a person with a disability who requires a reasonable accommodation in order to participate in this program, please contact Leslie Gannon in advance at (319) 335-6817 or leslie-gannon@uiowa.edu.