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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Faculty of Computer and Information Sciences
  2. Department of Data Science and Analytics (English)
  3. Course Structure Diagram with Credits
  4. Natural Language Processing and Text Analytics
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
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Last Updated: 21/07/2026

Code - Course Title Course Type Laboratory + Practice ECTS
VBA307 - Natural Language Processing and Text Analytics V. SEMESTER 3 +0 5.0
Language of Instruction İngilizce
Course Type Required Courses
Course Instructor(s) ARAŞ. GÖR. DR. ÖNDER DORAK
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites
Courses Recomended
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Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Text Preprocessing: Normalization and tokenization
Week - 2 Stemming and lemmatization techniques
Week - 3 Stop word removal and regular expressions
Week - 4 Text Representation: Bag-of-words models
Week - 5 Calculating TF-IDF matrices
Week - 6 Training word embeddings (Word2Vec, GloVe)
Week - 7 N-gram modeling structures
Week - 8 NLP Applications: Building sentiment analysis classifiers
Week - 9 Conducting topic modeling (LDA)
Week - 10 Implementing named entity recognition (NER)
Week - 11 Text summarization approaches
Week - 12 Advanced NLP Concepts: Sequence modeling for text
Week - 13 Evaluating NLP model performance
Week - 14 Handling multi-lingual text data

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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