Dec 05, 2025  
2025-2026 Undergraduate Catalog 
    
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2025-2026 Undergraduate Catalog
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MLAS 350 - Data Structures for Machine Learning

Credits: 3

This course will cover the design, development, and employment of data structures and algorithms with an emphasis on time-space complexity. Data structure processing and computational processing problems related to the following time-space problems will be explored: constant, logarithmic, cubic, quadratic, polynomial, and exponential. Additionally, students will leverage Bachmann-Landau notation to describe time-space complexity.

Repeat for Credit
N

Requisites
Prerequisite: MLAS 200 and CYBR 335

Typically Offered
Spring

K-State 8
Empirical and Quantitative Reasoning


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