Akademik Dersler - İçerik

Weeks	Topics
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).