Symbolische Programmiersprache Wintersemester 24/25

Undergraduate course, Ludwig-Maximilians-Universität München, 13 Fakultät für Sprach- und Literaturwissenschaften, Department II, Centrum für Informations- und Sprachverarbeitung, 2024

Serve as: Teacher

Teacher (exercise part): Dr. Robert Litschko, Beiduo Chen

Course Description

This course is about (Python) coding, language processing and some machine learning.

  1. Fundamentals:
  • Python fundamentals, including (Unit) Tests

  • Object-oriented programming in Python

  1. NLP (and IR) foundations:
  • How to represent text, corpora and NLP pre-processing in NLTK

  • Syntactic processing

  • Lexical semantic processing

  • Document-level processing (Information Retrieval, IR): web crawling, tf-idf, search engine

  1. ML: Machine Learning, supervised and unsupervised learning algorithms
  • Classification with kNN and Naïve Bayes

  • Clustering with k-means und Brown algorithm

Exercise for Symbolische Programmiersprache.

Course Schedule:

Week 1: Course Intro, Python fundamentals and Python Tests

Week 2: Object-oriented programming I, Python fundamentals II

Week 3: Object-oriented programming II, Regular expressions

Week 4: NLTK I: Corpus Linguistics, Representing documents

Week 5: NLTK II: Corpora and Preprocessing

Week 6: Syntax: POS tagging

Week 7: Document-level Processing

Week 8: Lexical Semantics (Wordnet and WSD)

Week 9: Machine Learning, Clustering

Week 10: Machine Learning, Classification (kNN) and Probability theory

Week 11: Naive Bayes

Week 12: Probeklausur - trial exam, Summary and Q&A

Week 13+14: Exercise and Q&A hours

Final Evaluation:

  • Mode: Written Exam (in person), closed-book (no material or tools allowed)
  • Duration: 45 min (Vorlesung/lecture exam) + 45 min (Übung/exercise exam)