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Courses - Spring 2024
CMSC
Computer Science Department Site
Open Seats as of
10/11/2024 at 10:30 AM
CMSC498Y
(Perm Req)
Selected Topics in Computer Science; Statistical Inference and Machine Learning Methods for Genomics Data
Credits: 3
Grad Meth: Reg
Prerequisites: Minimum grade of C- in CMSC351 and minimum grade of C- in any STAT400-level course; or DATA400; or ENEE324.

Covers statistical inference and machine learning methods for analyzing genomic data. Examples of topics covered will include maximum likelihood(including composite and pseudo-likelihood functions), expectation-maximization, clustering algorithms, hidden markov models, statistical testing, MCMC and variational inference. Our focus will be on how these techniques are utilized to solve biological problems and the practical challenges that arise when analyzing large genomic data sets.