Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Faculty Of Computer And Information Technologies
  • Artificial Intelligence And Machine Learning Pr. (English)
  • Course Structure Diagram with Credits
  • Probability
  • Learning Outcomes & Program Qualifications
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load
0 : Does not support   1 : Low-level support   2 : Mid-level support   3 : Top level support
Learning Outcomes123456789101112
Solve probability problems in complex sample spaces using combinatorial analysis and counting techniques.132102111000
Solve conditional probability problems by applying Bayes’ Theorem and adapt it to classification problems in artificial intelligence.232313121012
Determine the probability distribution (discrete/continuous) of a random variable and mathematically calculate its expected value and variance.132303231011
Can explain the linear relationship between multiple random variables using the concepts of covariance and correlation, and interpret the correlation matrix.------------
Can estimate the asymptotic behavior of the sums or means of independent random variables using the Central Limit Theorem.------------
Can convert simple systems into state-transition diagrams using Markov Chains and analyze steady-state probabilities.132303231011
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  • PhD / Proficiency in Art
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