Section outline

    • About the course         

    • Lectures 

    • The course syllabus.

      Topic
      Lectures
      1
      Syllabus and obligations; overview of artificial intelligence
      2 Nature inspired computation, genetic algorithms
      3
      Predictive modeling
      4 Bias, variance, and generalization error
      5
      Feature selection and representation learning
      6
      Neural networks
      7
      Natural language processing
      8
      Ensemble learning
       9 Kernel methods
      10
      Model explanation and understanding
      11
      Reinforcement learning


    • Exams 

    • Lab work (general)

    • Link to the code repository

    • Lab work (assignment 1) 

    • Lab work (assignment 2) 

    • Additional material                                                                                                                        

    • Quizzes