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4502. Big Data Analytics

3.00 credits

Prerequisites: CSE 3500; MATH 2210; open only to students in the School of Engineering and declared Computer Science and Analytics minors

Grading Basis: Graded

Focuses on basic concepts of data science and big data analytics. Different algorithmic techniques employed to process data will be discussed. Specific topics include: Parallel and out-of-core algorithms and data structures, rules mining, clustering algorithms, text mining, string algorithms, data reduction techniques, and learning algorithms. Applications such as motif search, k-locus association, k-mer counting, error correction, sequence assembly, genotype-phenotype correlations, etc. will be investigated.


Last Refreshed: 20-SEP-19 05.20.20.002631 AM
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Term Campus Instruction Mode Instructor Section Session Schedule Location Enrollment Notes
Fall 2019 Storrs In Person Rajasekaran, Sanguthevar 001 Reg TuTh 2:00pm‑3:15pm
UTEB 175 32/40 Combined with CSE 5717-001
Spring 2020 Storrs In Person Wei, Wei 001 Reg TuTh 11:00am‑12:15pm
0/40