Fall 2026 (Sep8-Dec9)
Faculty of Computer Science
Dalhousie University
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[ http://web.cs.dal.ca/~vlado/csci6509/coursecalendar.html ]
Fall 2026 (Sep8-Dec9) Faculty of Computer Science Dalhousie University |
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
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6 7 8 9 10 11 12 w1 4 5 6 7 8 9 10 w5 8 9 10 11 12 13 14 rw 6 7 8 9 10 11 12 wD
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| # | Date | Title | |
|---|---|---|---|
| Tu Sep 8 | Class cancelled on Tuesday | ||
| Part I: Introduction | |||
| 1 | Th Sep 10 | Course 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: Syllabus (PDF), slides, lecture notes. Reading: [JM] Ch.1 | A0 out |
| 2 | Fr Sep 11 | Course Project
Why is NLP hard? Ambiguities at different levels of NLP. About Course Project: topics and teams, deliverables, P0, P1, P, R. Files: slides, lecture notes. | |
| Part II: Stream-based Text Processing | |||
| 3 | Tu Sep 15 | Finite Automata Review
Part II: Stream-based Text Processing: Review of Finite Automata. Deterministic Finite Automata (DFA). Non-deterministic Finite Automata (NFA), and their use in NLP. NFA-to-DFA conversion. (Reading: Chapter 2 [JM]) Files: slides, lecture notes. Reading: [JM] Ch.2 | |
| 4 | Th Sep 17 | Regular Expressions and Perl Processing
NFA-to-DFA conversion (continued). Review of Regular Expressions. Introductionj to Perl. Regular Expressions (RegEx) use in Perl. Files: slides, lecture notes. Reading: On timberlea server `man perlretut' and `man perlre', or perlretut and perlre | |
| L1 | Fr Sep 18 | 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. | A1 out |
| 5 | Tu Sep 22 | RegEx Based Processing Examples
Regular expressions in Perl and basic text processing; counting words ex., regex matching, counting sentences, advanced regex features, regex substitutions, letter frequencies ex. Files: slides, lecture notes. | |
| Tu Sep 22 | Last day to add/drop courses | A0 due | |
| 6 | Th Sep 24 | Characters, Words, and Tokens
Regular expressions in Python. More tokenizer examples. BPE (Byte-Pair Encoding) tokenizer. Characters and Unicode. Word counting. Files: slides, lecture notes. | |
| L2 | Fr Sep 25 | Lab 2: Regular Expressions and Perl Tutorial 2
Regular expressions in Perl, Perl: basic I/O. Files: lab notes, slides. | |
| Fr Sep 25 | P0 Project Topic Proposal due | P0 due | |
| 7 | Tu Sep 29 | Elements of Morphology, Information Retrieval
Zipf's Law; Elements of Morphology: morphemes, stems, affixes, tokenization, stemming, lematization, morphological processes. Elements of Information Retrieval: Vector Space Model. Some interesting links: Lucene, IR book by Manning, Raghavan, and Schutze. IR Evaluation: precision, recall, F-measure, precision-recall curve. Interpolated Precision-Recall curve. Files: slides, lecture notes. | |
| We Sep 30 | National Day for Truth and Reconciliation, University closed | ||
| 8 | Th Oct 1 | Similarity-based Classification
Text Classification as Text Mining task. Evaluation methods for classification: training error, train-and-test, and n-fold cross-validation. Similarity-based text classification. Text Clustering, brief description. Similarity-based Text Classification, CNG classification. CNG classification method for authorship attribution. N-gram extraction implementation examples. Files: slides, lecture notes. | |
| L3 | Fr Oct 2 | Lab 3: Git and GitLab Tutorial Files: lab notes, slides. | A1 due |
| Part III: Probabilistic and Machine Learning Approach to NLP | |||
| 9 | Tu Oct 6 | P0 Topics Discussion
Project discussions: P-01, P-02, P-03, P-04, P-05, P-06, P-07, P-08, P-09, P-10, P-11, P-12, P-13, P-14, P-15, P-16, P-18, P-19, P-22. Introduction to Probabilistic NLP. Logical vs Plausible reasoning. Review of elements of probability theory. Bayes Theorem. Files: P0 slides, slides, lecture notes. | |
| We Oct 7 | Last day to drop classes without "W", change audit to credit or vv. | ||
| 10 | Th Oct 8 | Introduction to Probabilistic NLP
P0 Discussion (2): P-17, P-23, P-24, P-25. Bayesian inference and generative models; elements of probabilistic modeling and computational tasks; joint distribution model; fully independent model (started). Files: P0 slides #26, slides, lecture notes. | |
| L4 | Fr Oct 9 | Lab 4: Python NLTK Tutorial 1 Files: lab notes, slides. | |
| Mo Oct 12 | Thanksgiving Day, University closed | ||
| 11 | Tu Oct 13 | Naive Bayes Model; N-gram Model
P0 Discussion (3): P-21. Fully independent model (finished). Naive Bayes model: derivation, assumption, graphical representation, example, variations for text classification. N-gram Model: langauge modelling, assumption, Markov Chain comparison, Files: slides, lecture notes, P0 slides #31. | |
| 12 | Th Oct 15 | Smoothing; POS Tags Files: slides, lecture notes. | |
| L5 | Fr Oct 16 | Lab 5: Python NLTK Tutorial 2 Files: lab notes, slides. | A2 out |
| 13 | Tu Oct 20 | POS Tagging and Hidden Markov Model Files: slides, lecture notes. | |
| 14 | Th Oct 22 | Bayesian Networks and HMM Inference | |
| L6 | Fr Oct 23 | Lab 6: Python NLTK Tutorial 3: POS Tagging and Other Tasks | A2 due |
| 15 | Tu Oct 27 | Sum-Product Algorithms | |
| 16 | Th Oct 29 | Naive Bayes Model and Logistic Regression | |
| L8 | Fr Oct 30 | Lab 7: Python Tutorial with PyTorch | |
| Fr Oct 30 | P1 Project Statement due | P1 due | |
| Part IV: Deep Learning Approach to NLP | |||
| 17 | Tu Nov 3 | Neural Networks and NLP | |
| 18 | Th Nov 5 | Deep Learning Architectures for NLP | |
| Th Nov 5 | Last day to drop classes with "W" | ||
| L9 | Fr Nov 6 | Lab 8: Hugging Face Tutorial | |
| Mo Nov 9 | Fall Study Break Nov 9-13, no classes, University open except Wed | ||
| We Nov 11 | Remembrance Day, University closed | ||
| Part V: Syntactic and Semantic Processing | |||
| 19 | Tu Nov 17 | Syntax Formalisms Review | |
| 20 | Th Nov 19 | Syntax of Natural Languages | |
| L | Fr Nov 20 | Lab | |
| 21 | Tu Nov 24 | Probabilistic Context-Free Grammar | |
| 22 | Th Nov 26 | DCG and Unification-based Grammars | |
| L | Fr Nov 27 | Lab | |
| 23 | Tu Dec 1 | Chart Parsing | |
| 24 | Th Dec 3 | Elements of Semantics | |
| L | Fr Dec 4 | Lab | |
| Part V: Student Presentations | |||
| Mo Dec 7 | Student Presentations | ||
| Tu Dec 8 | Student Presentations (Monday schedule) | ||
| We Dec 9 | Classes end, Report due | Report due | |
| Final Exam | |||
| Su Dec 20 | Final Exam (12:00-15:00)
Final exam, duration 3 hours, starting at 12:00, Dalplex. Exams schedule URL: https://www.dal.ca/exams/halifax-exam-schedule.html | F.Exam | |