Akademik Dersler - Tanıtım

Last Updated: 23/06/2026

Code - Course Title	Course Type	Laboratory + Practice	ECTS
BVA221 - Natural Language Processing	III. SEMESTER	2 +1	3.0

Language of Instruction	Türkçe
Course Type	Area Elective Courses
Course Instructor(s)	ÖĞR. GÖR. AHMET MÜCAHİD ARVASİ
Mode of Delivery	Face to face
Place of Delivery
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Prerequisites	There are no prerequisites or corequisites for this course.
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Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Introduction to Natural Language Processing, Basic Concepts, and Elements of Language
Week - 2		Regular Expressions and Text Preprocessing (Tokenization, Stemming, Lemmatization)
Week - 3		Syntactic Analysis and Morphology
Week - 4		Introduction to Language Models and N-Gram Models
Week - 5		Statistical Natural Language Processing: Probability Theory and Naive Bayes Classifier
Week - 6		Text Representation and Vector Space Models: TF-IDF (Term Frequency - Inverse Document Frequency)
Week - 7		Finding Similarities Between Texts: Cosine Similarity and Jaccard Index
Week - 8		Midterm Exam
Week - 9		Text Classification Applications with Machine Learning (Sentiment Analysis, Spam Detection)
Week - 10		Text Clustering and Topic Modeling (LDA)
Week - 11		Introduction to Word Embeddings Models: Word2Vec and GloVe
Week - 12		Statistical and Extractive Text Summarization Techniques
Week - 13		Integration and Optimization of Machine Learning Algorithms (SVM, Decision Trees) on Text
Week - 14		Application of NLP Algorithms on Real-World Data and End-of-Term Project Presentations

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Assessment Method and Passing Requirements
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