Akademik Dersler - Tanıtım

Last Updated: 03/10/2025

Code - Course Title	Compulsory/Elective	Laboratory + Practice	ECTS
BVA205 - Natural Language Processing	III. SEMESTER	2 +2	5.0

Language of Instruction	Türkçe
Course Type	Required Courses
Course Instructor(s)	PROF. DR. ALPER TOLGA KUMTEPE
Mode of Delivery	Face to face
Place of Delivery
Used Educational Platforms
Prerequisites	Basic Mathematical Knowledge
Courses Recomended	Basic Mathematical Knowledge
Recommended Resources	Faculty Recommendation
Work Placement	N/A
Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Course introduction and fundamentals of NLP.
Week - 2		Text preprocessing techniques (tokenization, stopwords, lemmatization).
Week - 3		Syntactic analysis: N-grams and language models.
Week - 4		Word representations and embeddings (Word2Vec, GloVe).
Week - 5		Distributional semantics and vector space models.
Week - 6		Text classification (Naive Bayes, Logistic Regression, SVM).
Week - 7		Introduction to deep learning for NLP (RNN, LSTM, GRU).
Week - 8		Sentiment analysis and applications.
Week - 9		Language modeling and text generation.
Week - 10		Transformer architecture and self-attention.
Week - 11		BERT, GPT, and pre-trained language models.
Week - 12		Machine translation and multilingual NLP.
Week - 13		Applied NLP project (text classification, information extraction, etc.).
Week - 14		Current trends in NLP and ethical considerations (bias, explainability, data privacy).

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Assessment Method and Passing Requirements
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