섹션 개요

  • 공통

    모두 접기 모두 펼치기

    • About the course         

    • Announcements 포럼
    • Discussion forum 포럼
    • Course description and students obligations 2025/26 파일

    • 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 engineering 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
      14 Agentic systems
      15 Evaluation of intelligent systems

    • Lecture slides 2025/26 (updated continuously) 폴더

    • Exams 

    • Samples of written exams 폴더
    • A sample of oral exam questions 파일
      2021/01/15 21:24 업로드됨

    • Lab work (general)

    • Course repository URL

      Link to the code repository

    • Lab work (assignment 1) 

    • Lab work (assignment 2) 

    • Additional material                                                                                                                        

    • Data analyist is a top job URL
    • Data science cheatsheet URL
    • Numpy cheat sheet 파일
      2024/10/7 12:12 업로드됨
    • Pandas cheat sheet 파일
      2024/10/7 12:13 업로드됨

    • Quizzes                                                                                                                                            

    • Quiz 1 퀴즈
    • Quiz 2 퀴즈
    • Quiz 3 퀴즈
    • Quiz 4 퀴즈
    • Quiz 5 퀴즈