CMSC 402 - Big Data Analytics

Institution:

Shippensburg University of Pennsylvania

Subject:

Description:

We are living in data-intensive world. Efficiently extracting, interpreting, and learning from very large datasets requires efficient and scalable algorithms as well as new data management technologies. Machine learning techniques and high performance computing make the efficient analysis of large volumes of data. In this course we explore big dataset analysis techniques and apply it to the distributed. This course is highly interactive. Students are expected to make use of technologies to design highly scalable systems that can process and analyze Big Data for a variety of scientific, social, and environmental challenges.

Credits:

4.00

Credit Hours:

Prerequisites:

CMSC 310 (Grade of C or Higher) and MATH 217

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

08/15/2019 - 08/25/2024 

Institution Website:

www.ship.edu/

Phone Number:

(717) 477-7447

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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