Dalhousie University    [  http://web.cs.dal.ca/~vlado/csci6509/coursecalendar.html  ]
Fall 2025 (Sep23-Dec9)
Faculty of Computer Science
Dalhousie University

CSCI 4152/6509 — Course Calendar (tentative)

[ Home | Calendar | Project | Login | Login required: Misc | A0 ]
      September              October                  November                  December      
Su Mo Tu We Th Fr Sa    Su Mo Tu We Th Fr Sa    Su Mo Tu We Th Fr Sa     Su Mo Tu We Th Fr Sa
    1  2  3  4  5  6              1  2  3  4 w2                    1 w6      1  2  3  4  5  6 w10
 7  8  9 10 11 12 13     5  6  7  8  9 10 11 w3  2  3  4  5  6  7  8 w7   7  8  9 10 11 12 13 w+/ex11-
14 15 16 17 18 19 20    12 13 14 15 16 17 18 w4  9 10 11 12 13 14 15 rw  14 15 16 17 18 19 20 ex
21 22 23 24 25 26 27 w1 19 20 21 22 23 24 25 w5 16 17 18 19 20 21 22 w8  21 22 23 24 25 26 27 ex-21
28 29 30             w2 26 27 28 29 30 31    w6 23 24 25 26 27 28 29 w9  28 29 30 31         
                                                30                   w10                      
#DateTitle 
  Part I: Introduction
1 Tu Sep 23Course Introduction
Course introduction: logistics, administrivia, references, evaluation, policies, schedule; Introduction to NLP (reading Ch.1 [JM]): natural language and other languages, NLP applications, NLP as a research area, NLP Research Links and NLP Anthology http://aclweb.org/anthology/. Short history of NLP. NLP methodology overview. Levels of NLP.
Files: slides, lecture notes. Reading: [JM] Ch.1
 
  Part II: Stream-based Text Processing
2 Th Sep 25 Sources of Complexity in NLP, Course Project, Finite Automata Review (start)
Why is NLP generally hard. Ambiguities at different levels of NLP. About Course Project: topics and teams, deliverables, P0, P1, P, R. Part II: Stream-based Text Processing: Deterministic and Non-deterministic Automata. (Reading: Chapter 2 [JM]) Review of Deterministic Finite Automata (DFA) (start).
Files: slides, lecture notes, Syllabus (PDF).
 
L1 Mo Sep 29 Lab 1: FCS Computing Environment, Perl Tutorial 1
Logging in using CSID, timberlea environment; Introduction to Perl programming language: basic syntax, variables, string literals, subroutines.
Files: lab notes, slides.
 
  Tu Sep 30National Day for Truth and Reconciliation, University closed  
3 Th Oct  2Finite Automata Review
Review of Non-deterministic Finite Automata (NFA), and their use in NLP. NFA-to-DFA conversion. Review of regular expressions.
Files: slides, lecture notes. Reading: [JM] Ch.2
 
L2 Mo Oct  6 Lab 2: Perl Tutorial 2
Regular expressions in Perl, Perl: basic I/O.
Files: lab notes, slides.
 
4 Tu Oct  7 Basic NLP with Perl
Introduction to Perl, main Perl features, syntactic elements, program examples.
Files: slides, lecture notes. Reading: On timberlea server `man perlretut' and `man perlre', or perlretut and perlre
 
5 Th Oct  9 N-grams and Morphology
Regular expressions in Perl and basic text processing; Text processing examples: tokenization, counting letters. Elements of Morphology: reading: Section 3.1 [JM]; morphemes, stems, affixes, tokenization, stemming, lematization, morphological processes. Characters, Words, and N-grams: counting words, Zipf's law. Perl examples with n-gram collection.
Files: slides, lecture notes. Reading: Section 3.1 [JM]
A0 out
  Fr Oct 10 P0 Project Topic Proposal due P0 due
  Mo Oct 13Thanksgiving Day, University closed  
6 Tu Oct 14 Text Similarity and Applications
N-gram collection (finished). Elements of Information Retrieval: Vector Space Model. Some interesting links: Lucene, IR book by Manning, Raghavan, and Schutze.
Files: slides, lecture notes. Reading: [JM] 23.1 (Information Retrieval), [MS] Ch.15 (Topics in Information Retrieval)
 
7 Th Oct 16 Text Classification
IR Evaluation: precision, recall, F-measure, precision-recall curve. Interpolated Precision-Recall curve. Text mining. Text Classification: classifier evaluation precision, recall, and F-measure in classification.
Files: slides, lecture notes.
A0 due
L3 Fr Oct 17 Lab 3: Perl Tutorial 3
Note: Lab 3 (Perl Tutorial 3) is provided for reference only. It is not required to be completed.
Files: lab notes, slides.
 
L4 Mo Oct 20 Lab 4: Git and GitLab Tutorial
Introduction to GitLab and Git; adding and modifying files, setting up SSH key, add, commit, and push commands, checkout; creating branches and working collaboratively, pull, merge, resolving conflicts.
Files: lab notes, slides.
 
8 Tu Oct 21 Similarity-based Classification Files: slides, lecture notes. 
  Part III: Probabilistic and Machine Learning Approach to NLP
  Labs: Python, NLTK, PyTorch  
  P0 Topics Discussion; Introduction to Probabilistic Modeling  
  Basic Probabilistic Models  
  Naive Bayes Model  
  N-gram Model  
  N-gram Model Smoothing  
  POS Tagging and Hidden Markov Model  
  Inference with HMMs  
  Efficient Inference for Bayesian Networks and HMMs  
  Fr Nov  7 P1 Project Statement due P1 due
  Neural Networks and NLP  
  Deep Learning and NLP  
  Part IV: Syntactic Processing
  Labs: To Be Decided (possibly Prolog)  
  DCG and PCFG  
  DCG and PCFG Grammars  
  Syntax of Natural Languages; CKY Algorithm  
  CKY Algorithm and PCFGs  
  Part V: Student Presentations
  Student Presentations  
  We Dec 10Classes end, Report due Report due
  Final Exam
  ?? Dec  ?Final Exam (TBA)
Final exam, 3 hours; date, time, and location to be announced. Exam period: Dec 11 to Dec 21 (3 hour final exam); Exams schedule URL: http://www.dal.ca/academics/exam_schedule/halifax_campus_exam_schedule.html
F.Exam

Maintained by: Vlado Keselj, last update: 20-Oct-2025