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Students in this cohort of The Data Mine will learn the essentials of data visualization, which is a key component of data science and a common thread across majors and disciplines. Students will work with a number of data visualization tools as they learn to choose the right visual representation of data based on the type of data. Guest speakers and field trips to different departments with data visualization needs are key components of this cohort. Students will gain hands-on experience in transforming data into insight, creating a natural platform to apply critical thinking to their data mining knowledge. Research projects will include projects in data science, data visualization, machine learning, databases, big data and virtual/augmented reality.

Additional information can be found at datamine.purdue.edu/data-visualization.  

Eligibility

Any undergraduate student with an interest in the Data Sciences

Residential Component

  • Incoming First-Year Students from this learning community must reside in Hillenbrand Hall
  • A signed housing contract is required to apply to this learning community.
  • 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

Full Academic Year

Associated Classes

Fall

  • CGT 27000 Introduction To Data Visualization:
    • For CGT majors: CGT 27000 (3 credits)
    • For CGT non-majors: CGT 27000 (3 credits)
  • CGT 29000 (1 credit) Topics In Visualization
  • STAT 19000, 29000, 39000, or 49000 (1 credit) The Data Mine I or III or V or VII

Spring

  • CGT 29000 (3 credits) Data Visualization II 
  • STAT 19000, 29000, 39000, or 49000 (1 credit) The Data Mine II or IV or VI or VIII

Additional information can be found at datamine.purdue.edu/data-visualization.

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.

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