Class 1 |
Introduction |

Class 2 |
Probability Theory |

Class 3 |
Graph Theory |

Class 4 |
Bayesian Classifiers |

Class 5 |
Hidden Markov Models |

Class 6 |
Markov Random Fields |

Class 7 |
Bayesian networks: representation and inference |

Class 8 |
Bayesian networks: learning |

Class 9 |
Mid Term Exam |

Class 10 |
Project proposals / Dynamic and Temporal Bayesian networks |

Class 11 |
Decision graphs |

Class 12 |
MDPs |

Class 13 |
Relational probabilistic graphical models |

Class 14 |
Causal models / Final project - preliminary report |

Class 15 |
Final project - presentation and final report |