Interdisciplinary Data Analytics Practicum

Catalog description

Credits 3. 3 Lecture Hours. . Application of data analytic methods and technologies in domain-based problems with real-world data; use of relevant machine learning platforms and open source tools; organization of project activities to meet goals; written and oral communication skills and methods for effective collaboration in teams with members drawn from varied technical disciplines. Prerequisite: STAT 404 , ISTM 313 , ISTM 315 , PETE 404 , GEOP 361 , CSCE 310 , or CSCE 314 ; STAT 408 , SCMT 305 , ECEN 360 , STAT 315 , CSCE 305 , GEOL 360 , CSCE 305 , CSCE 320/STAT 335 , or STAT335; STAT 436 , STAT 421 , CSCE 421 , ISTM 360 , or PETE 419 .