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COM SCI 112 · CS 112Modeling Uncertainty in Information Systems

Computer Science · 4 units · Undergraduate upper division (100-199)

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Designed for juniors/seniors. Probability and stochastic process models as applied in computer science. Basic methodological tools include random variables, conditional probability, expectation and higher moments, Bayes theorem, Markov chains. Applications include probabilistic algorithms, evidential reasoning, analysis of algorithms and data structures, reliability, communication protocol and queueing models.

Letter grading.

When it runs

Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.

Requisites

Official UCLA wording

Enforced requisites: course 111 and one course from Civil Engineering 110, Electrical Engineering 131A, Mathematics 170A, or Statistics 100A.

BruinTree reads · Prerequisite

confidence 1.00 · from text
all of
  • COM SCI 111
  • 1 of
    • C&EE 110
    • EC ENGR 131A
    • MATH 170A
    • STATS 100A

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About COM SCI 112. We read UCLA’s requisite wording by machine, and it gets things wrong.

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Requires

Everything that has to come before this course, not just the courses named in the requisite above.

COM SCI 112

  • COM SCI 111Operating Systems Principles
    • COM SCI 32Introduction to Computer Science II
      • COM SCI 31Introduction to Computer Science I
    • COM SCI 33Introduction to Computer Organization
      • COM SCI 32Introduction to Computer Science IIanother path to it
    • COM SCI 35LSoftware Construction
      • COM SCI 31Introduction to Computer Science Ianother path to it
      • COM SCI 32Introduction to Computer Science IIanother path to it
  • C&EE 110Introduction to Probability and Statistics for Engineers
    • MATH 32ACalculus of Several Variables
      • MATH 31ADifferential and Integral Calculus1 more beneath
    • MATH 33ALinear Algebra and Applications
      • MATH 3BCalculus for Life Sciences Students1 more beneath
      • MATH 31BIntegration and Infinite Seriesanother path to it
      • MATH 32ACalculus of Several Variablesanother path to it
  • EC ENGR 131AProbability and Statistics
    • MATH 32BCalculus of Several Variables
      • MATH 31BIntegration and Infinite Series
      • MATH 32ACalculus of Several Variablesanother path to it
    • MATH 33BDifferential Equations
      • MATH 31BIntegration and Infinite Seriesanother path to it
  • MATH 170AProbability Theory I
    • MATH 32BCalculus of Several Variablesanother path to it
    • MATH 33ALinear Algebra and Applicationsanother path to it
    • MATH 131AAnalysis
      • MATH 32BCalculus of Several Variablesanother path to it
      • MATH 33BDifferential Equationsanother path to it
  • STATS 100AIntroduction to Probability
    • MATH 32BCalculus of Several Variablesanother path to it
    • MATH 33ALinear Algebra and Applicationsanother path to it

5 direct requisites. Showing 30 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.

Unlocks

What this course is a requisite for, and what those courses lead to in turn.

COM SCI 112

  • COM SCI 212AQueueing Systems Theory
  • COM SCI 218Advanced Computer Networks
  • COM SCI 246Web Information Management
  • COM SCI 262ALearning and Reasoning with Bayesian Networks
    • COM SCI 262ZCurrent Topics in Cognitive Systems
    • STATS M241Current Topics in Causal Modeling, Inference, and Reasoning

4 courses list this as a requisite. The whole downstream is here — 6 courses over 2 levels. Every course here opens its own tree.