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  • skills
  • education
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    • Masters in Artificial Intelligence

    Artificial Intelligence and Machine Learning

    1st Semester
    Intelligent Agents
  • Introduction to agent-based computing
  • Agent Interactions
  • Agent design and implementation
    • Foundations of Artificial Intelligence
  • Introduction to AI
  • Search and representing Knowledge
  • Reasoning under uncertainity and machine learning
    • Machine Learning Technologies
  • Tools in Machine Learning
  • Supervised and unsupervised learning
  • Deep Learning and case Studies
    • 2nd Semester
    Algorithmic game theory
  • Basic Game theory Concepts
  • Mechanism Design Without and With money
  • Applications
    • Computational Finance
  • Data Driven Models
  • foundations of BlockChain
    • Simulation Modelling For Computer Science
  • Modelling Platforms and Environments
  • Agent Based Models and General equilibrium modelling
  • Finite Elements and networks
  • Monte Carlo methods
  • Scientific Computing Using Python
    • Computer Vision
  • The human-eye Brain System
  • Image Formation and Models
  • 2D Shape Representation and local features
  • 3D vision systems