This syllabus outlines the key topics covered in the course "NLP Fundamentals". If you are interested in learning more about natural language processing, check out our Introduction to NLP.

Course Overview

The course is designed to provide a comprehensive introduction to the field of natural language processing (NLP). It covers both theoretical and practical aspects of NLP, including:

  • Language models
  • Text processing
  • Sentiment analysis
  • Machine translation
  • Information extraction

Course Topics

  • Introduction to NLP

    • What is NLP?
    • History of NLP
    • Applications of NLP

  • Language Models

    • Types of language models
    • Pre-trained language models
    • Fine-tuning language models

  • Text Processing

    • Tokenization
    • Part-of-speech tagging
    • Named entity recognition

  • Sentiment Analysis

    • Sentiment classification
    • Sentiment analysis applications

  • Machine Translation

    • Statistical machine translation
    • Neural machine translation

  • Information Extraction

    • Named entity recognition
    • Relation extraction
    • Event extraction

Course Materials

  • Lecture Notes: Access the lecture notes for each module here.
  • Assignments: Complete the assignments and submit them here.

Natural Language Processing

If you have any questions or need further assistance, please don't hesitate to contact the instructor. Good luck with your studies in NLP!