Introduction
This course provides an introduction to computational methods used in language analysis. It bridges linguistics and computer science, highlighting how algorithms, corpora, and NLP tools can process and analyze human language data.
Unique Selling Propositions
Practical exposure to NLP tools and techniques.
Bridging theory with hands-on computational applications.
Ideal foundation for advanced studies in AI and linguistics.
Objectives and Learning Outcomes
Understand core concepts of computational linguistics and NLP.
Explore applications of computational models in linguistic analysis.
Gain introductory skills in corpus and text processing.
Key Topics / Related Concepts
Linguistic Data and Annotation
Natural Language Processing Basics
Computational Models of Syntax and Semantics
Activities and Learning Strategies
Tool demonstrations (e.g., POS tagging, parsing).
Guided text analysis exercises.
Short project on computational text exploration.
Participants / (Target Audience)
Undergraduate students, professionals, and teachers seeking to enhance spoken English proficiency.
Ms.Sidra Haroon Lecturer, Department of Linguistics and Communications, UMT, Lahore Qualification: M.Phil. Applied Linguistics; PhD (in progress) in English Linguistics Expertise: Corpus Linguistics, Computational Linguistics, and Semantic Prosody Analysis Experience: Over 14 years of teaching and research experience in applied and computational linguistics. Teaches undergraduate courses in Corpus Linguistics, Computational Linguistics, and Language Documentation. Supervises BS and MS theses involving corpus-based and computational methods. Skilled in SketchEngine, AntConc, LancsBox, and SPSS. Publications & Research: Published in HEC-recognized journals on corpus-based analysis, functional morphology, and semantic prosody. Presented research at international conferences in Bosnia, Italy, and Turkey.
