Section outline

    • Honor Code

      We encourage students to form study groups, and discuss the lecture and other materials. However, the work that you submit should be your own work. For the programming part you are allowed to use other solutions, algorithms but you must know their properties and also introduce your own contributions for completion of your project (e.g. input data manipulation, parameter changes, architectural changes).


    • Exams

        • First exam, June 10, 2024 at 3pm in PA
        • Second exam, June 20, 2024 at 12pm in P1
        • Third exam, September 6, 2024 at 10am in P22

    • The course syllabus.

      Topic
      Lectures
      1
      Syllabus and obligations
      2 Language and intelligence, a short overview of NLP
      3
      Text normalization
      4
      Sparse and dense word representations
      5
      Neural network and neural embeddings
      6 Convolutional and recurrent neural networks for text
      7
      Attention mechanism and transformer networks
      8
      Large language models for text classification (BERT)
      9
      Large generative language models (GPT and T5 families) and multimodal models
      10
      Prompt engineering and retrieval augmented generation
      11
      POS-tagging, dependency parsing, named entity recognition and semantic role labelling
      12
      Word senses and disambiguation
      13
      Affective computing
      14
      Machine translation
      16
      Summarization and question answering
      17
      Knowledge graphs for language
      18
      Guest lecture

  • Quizzes encourage continuous learning and review of covered topics. Together, in all quizzes, one shall acquire at least 50% of points. Only quizzes submitted on time count.; wrong answers bring negative points.

  • Lab sessions will start in the second week of semester (February 20, 2023).