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 AutoML
      11 Transformers for tabular data and time series
      12 Model explanation and understanding
      13 Reinforcement learning

    • Exams 

    • Lab work (general)

    • Link to the code repository

    • Lab work (assignment 1) 

    • Lab work (assignment 2) 

    • Additional material                                                                                                                        

    • Quizzes