Learning objectives
The aim of the course is to provide skills in the field of Python programming in the context of simple Natural Language Processing applications. At the end of the course the students: 1) will know the elementary data structures and basic programming constructs; 2) they will be able to modify and write programs written in Python that manipulate and analyze texts, acquiring useful skills for humanists. 3) They will know the basics of representing text on the computer.
Prerequisites
No requirements
Course unit content
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Full programme
1) Introduction to Text Mining:
- Text representation (ASCII)
- N-grams
- Tokenization
- Edit distance
- Hints about modern language models
2) Introduction to Python
- Variables and list
- For with iterators
- If instruction
- While cycle
- Dictionaries
- Read and write from files
Bibliography
- How to Think Like a Computer Scientist (Learning with Python): http://openbookproject.net/thinkcs/python/english3e/
- Python 101: http://python101.pythonlibrary.org/index.htm
-- Speech and Language Processing, Jurafsky (2023) (First chapter as introduction)
Teaching methods
Lecture in a computer lab to combine theoretical and practical activities.
Assessment methods and criteria
The final exam will consists into a practical project with Python to be realized as homework. Then the student will present his/her activity during an oral exam where the homework will be evaluated in terms of:
- Correctness
- Complexity
- Quality of the documentation
- Quality of the discussion
Moreover, during the oral presentation, the student will be evaluated in any part of the course programm with open questions or simple exercises.
Other information
The frequency of the lectures is highly suggested.
2030 agenda goals for sustainable development
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