???? 1?? Foundations of NLP

• Introduction to NLP

• Text preprocessing (tokenization, stemming, lemmatization)

• Stop-word removal

• Regular expressions

• N-grams

• Bag of Words (BoW)

• TF-IDF

• Text normalization

???? 2?? Linguistics in NLP

• Morphology

• Syntax

• Semantics

• Pragmatics

• Discourse analysis

• Constituency & Dependency parsing

• Part-of-Speech (POS) tagging

• Named Entity Recognition (NER)

???? 3?? Classical Machine Learning for NLP

• Naive Bayes

• Logistic Regression

• Support Vector Machines (SVM)

• Hidden Markov Models (HMM)

• Conditional Random Fields (CRF)

• Feature engineering for text

???? 4?? Deep Learning for NLP

• Word embeddings (Word2Vec, GloVe, FastText)

• Neural language models

• Recurrent Neural Networks (RNN)

• LSTM & GRU

• Sequence-to-Sequence models

• Attention mechanism

• Transformer architecture

???? 5?? Large Language Models (LLMs)

• BERT

• GPT models

• T5

• Fine-tuning techniques

• Prompt engineering

• Instruction tuning

• RLHF (Reinforcement Learning from Human Feedback)

• Parameter-efficient fine-tuning (LoRA, adapters)

???? 6?? Retrieval-Augmented Generation (RAG)

• Dense retrieval

• Vector embeddings

• Vector databases

• Hybrid search

• Chunking strategies

• Token optimization

• Evaluation metrics for RAG systems

???? 7?? NLP Applications

• Sentiment analysis

• Text classification

• Machine translation

• Question answering systems

• Chatbots & conversational AI

• Text summarization

• Speech-to-text & text-to-speech

• Information extraction

???? 8?? Advanced / Enterprise NLP Topics

• Agentic AI systems

• Multi-agent orchestration

• Hallucination mitigation

• LLM evaluation frameworks

• AI governance & safety

• Bias detection & fairness

• Multilingual NLP

• Knowledge graphs + LLMs

• Domain adaptation

???? 9?? Evaluation & Metrics

• BLEU score

• ROUGE score

• Perplexity

• Precision / Recall / F1

• Human evaluation frameworks

• LLM benchmarking