Eskisehir Technical University Info Package Eskisehir Technical University Info Package
  • Info on the Institution
  • Info on Degree Programmes
  • Info for Students
  • Türkçe
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
  • Reinforcement Learning
  • Learning Outcomes
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load
  • Can formulate a problem as an MDP (Markov Decision Process).
  • Can derive the Bellman Expectation and Optimality equations.
  • Can implement tabular Q-Learning and SARSA algorithms using Python/NumPy.
  • Can explain the "Exploration vs. Exploitation" dilemma.
  • Can apply the Deep Q-Network (DQN) algorithm in Gym environments using Keras.
  • Can explain the fundamental logic behind Policy Gradient methods (e.g., REINFORCE).
  • Info on the Institution
  • Name and Adress
  • Academic Calendar
  • Academic Authorities
  • General Description
  • List of Programmes Offered
  • General Admission Requirements
  • Recognition of Prior Learning
  • Registration Procedures
  • ECTS Credit Allocation
  • Academic Guidance
  • Info on Degree Programmes
  • PhD / Proficiency in Art
  • Master's Degree
  • Bachelor's Degree
  • Associate Degree
  • Info for Students
  • Cost of living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Special Needs Students ı
  • Insurance
  • Financial Support for Students
  • Student Affairs Office
  • Info for Students
  • Learning Facilities
  • International Programmes r
  • Practical Information for Mobile Students
  • Language courses
  • Internships
  • Sports and Leisure Facilities
  • Student Associations