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5717. Big Data Analytics

3.00 credits

Prerequisites:

Grading Basis: Graded

Focuses on data science and big data analytics. Introduces basic concepts of data science and 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-DEC-24 05.20.17.275138 AM
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Section Class Number Notes Instructor Enrollment Session Instruction Mode
002 5982 Wei, Wei 18/30 Reg Online Synchronous