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SCTC 4351. Paradigms of Scientific Knowledge: Knowledge Discovery from Scientific Data. 3 Credit Hours.

This course is not offered every year.

The goal of this course is to teach science students the necessary skills for knowledge discovery from large collections of data. The course is designed to introduce students to various data mining algorithms and illustrate how they can be applied to real-life knowledge discovery problems in sciences. Case studies will be discussed that illustrate application of data mining systems in biology, chemistry and physics. One emphasis of the course will be in teaching students how to use various data mining software to solve various knowledge discovery problems. Through this course, students will develop abilities in problem solving and critical thinking, both of which are necessary for the practice of data mining. This will be accomplished by demonstrating the practical applications of each presented algorithm, by emphasizing each algorithm's limitations, and by assigning research-like course projects.

Class Restrictions: Must be enrolled in one of the following Classes: Junior 60 to 89 Credits, Senior 90 to 119 Credits, Senior/Fifth Year 120+ Credits.

Repeatability: This course may not be repeated for additional credits.

Pre-requisites:
CIS 1051|Minimum Grade of C-|May not be taken concurrently
OR CIS 1053|Minimum Grade of C-|May not be taken concurrently
OR CIS 1056|Minimum Grade of C-|May not be taken concurrently
OR CIS 1057|Minimum Grade of C-|May not be taken concurrently
OR CIS 1068|Minimum Grade of C-|May not be taken concurrently
OR CIS 1073|Minimum Grade of C-|May not be taken concurrently.

Natural Sciences, B.A.

http://bulletin.temple.edu/undergraduate/science-technology/biology/natural-sciences-ba/

...recommended that SCTC 1501 or SCTC 1502 be completed before SCTC 4351 or SCTC 4396...