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How does your map app on your phone know where a traffic jam is? How do we find patient zero in a medical epidemic? The purpose of this learning community is to provide an opportunity to learn how to develop systems that can be used to generate new knowledge that we can use to make important decisions that impact our lives on a daily basis. Uncover trends, patterns, or other information hidden in the big picture of big data. Learn the basics of working with data and the skills and knowledge to pursue multiple avenues in the continuum of data science: from management to analytics to applications related to engineering complex systems.

In the first semester, learn the fundamentals of data science: types of data, data lifecycle, transformation and visualization, and make evidence-based decisions in user-oriented engineering modeling and design problems. 

In the second semester, develop your skills to build and use analytical tools using MATLAB and Python to make new discoveries about how natural and built system work.   Learn how to gather, organize, and store big data sets and then build algorithms in a way that machines can autonomously process the data to generate information  we need when working on engineering projects. Discover how critical evaluation of information is used to make appropriate decisions and conclusions and, in the process, learn to know when the first question asked, isn’t the only question that needs to be answered. 

Join a cohort of first-year engineering students who will take five data-science themed courses together and participate in fun and educational co-curricular and extracurricular activities that are exclusive to our learning community.

Follow us on Instagram @engineeringworldofdata

dinner
Matt Painter
instructors
Students

Eligibility

  • First-time beginning students admitted to the First-Year Engineering Program or to Pre-ABE in the College of Agriculture
  • This LC is not available to Honors College participants - Honors College students will participate in the Goss Scholars Learning Community

Residential Component

  • Students from this learning community will reside in Shreve Hall, unless dual placed into Women in Engineering or athletics participation.
  • If you wish to also participate in Women in Engineering and want to live with WIE, be sure to preference WIE higher on your application
  • You will indicate your learning community housing preference within the learning community application. A signed housing contract is required to apply to this learning community.
  • Your roommate in most cases will be a member of the learning community
  • Completing a housing contract is a separate process from applying for a learning community

Duration

Full Academic Year

Associated Classes

Fall

ENGR 13100 - Transforming Ideas to Innovation 1

ILS    10300 - Introduction to Data Lifecycle Management

ENGL 10600 - First Year Composition – First Year Composition with Data Science Emphasis (optional based on AP scores or transfer credit)

Spring

ENGR 13200 - Transforming Ideas to Innovation 2 

ENGR 10300 - Computational Methods of Data Science for Engineers

 

Events and Activities Included:

Examples of community activities from previous years:

  • Data science and sports: Moneyball with Coach Matt Painter
  • Learning Python with Pythons: programming boot camp with animal management data and snakes
  • Dawn or Doom conference: workshop on presenting data effectively and lunch with keynote speaker
  • Field trip to Cummins Technical Center: simulation and product testing data management and analytics

Information above is subject to change. If you are placed in the LC, the associated courses will be on your schedule prior to you registering for the rest of your courses.

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