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
1 2 3 4 5 1 2 3 w4 1 2 3 4 5 6 7 w9 1 2 3 4 5 wC
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
13 14 15 16 17 18 19 w2 11 12 13 14 15 16 17 w6 15 16 17 18 19 20 21 wA 13 14 15 16 17 18 19
20 21 22 23 24 25 26 w3 18 19 20 21 22 23 24 w7 22 23 24 25 26 27 28 wB 20 21 22 23 24 25 26
27 28 29 30 w4 25 26 27 28 29 30 31 w8 29 30 wC 27 28 29 30 31
| # | Date | Title | |
|---|---|---|---|
| Tu Sep 8 | Class cancelled on Tuesday | ||
| Part I: Introduction | |||
| 1 | Th Sep 10 | Course Introduction Files: Syllabus (PDF), slides, lecture notes. | A0 out |
| 2 | Fr Sep 11 | Course Project Files: slides, lecture notes. | |
| Part II: Stream-based Text Processing | |||
| 3 | Tu Sep 15 | Finite Automata Review | |
| 4 | Th Sep 17 | Basic NLP with Perl | |
| L1 | Fr Sep 18 | Lab 1: FCS Computing Environment, Perl Tutorial 1 | |
| 5 | Tu Sep 22 | N-grams and Morphology | |
| Tu Sep 22 | Last day to add/drop courses | A0 due | |
| 6 | Th Sep 24 | Text Similarity and Applications | |
| L2 | Fr Sep 25 | Lab 2: Perl Tutorial 2 | |
| Fr Sep 25 | P0 Project Topic Proposal due | P0 due | |
| 7 | Tu Sep 29 | Text Classification | |
| We Sep 30 | National Day for Truth and Reconciliation, University closed | ||
| 8 | Th Oct 1 | Similarity-based Classification | |
| L3 | Fr Oct 2 | Lab 3: Perl Tutorial 3 | |
| Part III: Probabilistic and Machine Learning Approach to NLP | |||
| 9 | Tu Oct 6 | Introduction to Probabilistic NLP | |
| We Oct 7 | Last day to drop classes without "W", change audit to credit or vv. | ||
| 10 | Th Oct 8 | Naive Bayes Model | |
| L4 | Fr Oct 9 | Lab 4: Git and GitLab Tutorial | |
| Mo Oct 12 | Thanksgiving Day, University closed | ||
| 11 | Tu Oct 13 | N-gram Model and Markov Chain Model | |
| 12 | Th Oct 15 | POS Tagging and Hidden Markov Model | |
| L5 | Fr Oct 16 | Lab 5: Python NLTK Tutorial 1 | |
| 13 | Tu Oct 20 | P0 Topics Discussion | |
| 14 | Th Oct 22 | Bayesian Networks and HMM Inference | |
| L6 | Fr Oct 23 | Lab 6: Python Tutorial 2 | |
| 15 | Tu Oct 27 | Sum-Product Algorithms | |
| Part IV: Deep Learning Approach to NLP | |||
| 16 | Th Oct 29 | Neural Networks and NLP | |
| L8 | Fr Oct 30 | Lab 8: Python Tutorial with PyTorch | |
| Fr Oct 30 | P1 Project Statement due | P1 due | |
| 17 | Tu Nov 3 | Deep Learning Architectures for 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 9: 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 | |||
| ?? Dec ? | Final Exam (TBA)
Final exam, 3 hours; date, time, and location to be announced. Exam period: Dec 10 to Dec 20 (3 hour final exam); | F.Exam | |