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
  • Introduction to Optimization Theory
  • 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
Can calculate the gradient and Hessian matrix of a function and determine its convexity.133201330000
Can numerically solve simple unconstrained optimization problems using NumPy/SciPy.323201231011
Can explain the differences between Gradient Descent, Stochastic Gradient Descent, Momentum, and Adam optimizers.133301311111
Can compare second-order methods (Newton’s Method) and first-order methods (Gradient Descent).------------
Can solve equality-constrained problems using Lagrange Multipliers.133210130001
Can explain the meaning of the KKT conditions for inequality-constrained problems.133300130101
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