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Students in this cohort of The Data Mine will work in multidisciplinary teams of students to engage in research-based projects. Research teams are vertically-integrated in that they consist of first-year students, sophomores, juniors, seniors and graduate student mentors. Most projects in VIP last multiple years. Research undertaken by VIP teams include projects in  Electrical and Computer Engineering; Civil Engineering; Forestry; Earth, Atmospheric and Planetary Sciences; Libraries; Aeronautics and Astronautics, and more.

Eligibility

Any undergraduate student with interest in the Data Sciences.  The student background will help to determine the specific VIP research team which the student is admitted.

Residential Component

  • Students from this learning community must reside in Hillenbrand Hall
  • Information on this residence hall can be found here
  • Students who are required to reside in a different residence hall (e.g. due to the Honors College or athletics participation) or who do not sign a housing contract may not participate in 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

Fall and Spring semesters

Associated Classes

  1. STAT 19000 1 credit per semester -- The Data Mine I and II

  2. Enrollment in the appropriate course section of the VIP courses. Students may enroll in these courses for multiple semesters. 

  3. One course related to the students' and VIP teams' requirements each semester. Examples include:

Fall (most students will choose 1 course or something similar):

  • ECE 29500: Introduction to Data Science

  • CS 15900: Programming Applications for Engineers

  • CS 18000: Problem Solving And Object-Oriented Programming

  • ECE 26400: Advanced C Programming

Spring (most students will choose 1 course or something similar):

  • Software Engineering for Data Science and Machine Learning

  • Data Management and Visualization

  • Image Processing and Computer Vision for Machine Learning

Events and Activities Included:

  • Weekly dinners with LC participants
  • Tour of Purdue’s computational facilities
  • Social gatherings with LC members
  • Seminars by visiting speakers including practicing actuaries and data scientists
  • Meals with campus and community leaders
  • Game / recreation nights
  • Career and graduate school panels

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.

Learning Communities ERHT 1275 1st Street, West Lafayette, IN 47906 - (765) 494-5785 or (765) 494-8571, learningcommunities@purdue.edu

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