About the Earth, Atmospheric, and Planetary Sciences Cohort

As part of The Data Mine, students in this learning community work with large, complex data sets in the geosciences including atmospheric, planetary, geology and geophysics practices. Emphasis will be placed on using big data analysis tools in software and lab settings to study the nature of data in the geosciences. Students will use their data analysis skills to formulate a scientific question and propose and design a semester-length research project.

Eligibility

Any undergraduate student enrolled in the College of Science with an interest in the Data Sciences and Geosciences (first-year students and continuing students are both welcome)

Residential Component

• New Incoming Students: Living in Data Mine residential space is required unless you are in the Honors College or have other special accommodations needed.
• The Housing Reapplication process – Residents can opt into the Housing Reapplication Lottery from October 14 at 8:30 a.m. EDT to October 22 at 5 p.m. EDT in the Housing Portal.
• Your roommate (in most cases) will be a member of The Data Mine.
• If you want to live on campus, it is necessary to complete a housing contract. (Completing a housing contract is a separate process from applying for a learning community.)

Duration

Fall and spring semesters

Required classes

The information below is subject to change.
New incoming students should consider applying for the General or Corporate Partners cohorts. Pre-requisite or Co-requisite of EAPS 22700 is Calculus I.

Fall

• EAPS 22700 3 credits; section SC1: CRN 20565) Introduction to Atmospheric Observation and Measurements
• TDM 10100, 20100, 30100, 40100 (1 credit; 5 sections available) The Data Mine I, III, V, or VII

Spring

• TDM 10200, 20200, 30200, 40200 (1 credit; 5 sections available) The Data Mine II, IV, VI, or VIII

Events and Activities

• Weekly dinners with Data Mine participants
• Faculty and TA office hours onsite in Hillenbrand
• Seminars by visiting speakers, including practicing data scientists
• Social gatherings with Data Mine members
• Meals with campus and community leaders
• Game / recreation nights
• Career and graduate school panels
• Hackathons / data competitions
• Professional development activities
• Tour of Purdue’s computational facilities