| S.No |
Topic |
Sub-Topics |
| 1 | Introduction to NLP | Definition, History, Applications, Challenges, Industry trends |
| 2 | Text Preprocessing | Tokenization, Stopword removal, Stemming, Lemmatization, Normalization |
| 3 | Bag of Words & TF-IDF | Vectorization, Frequency count, TF-IDF, Advantages, Limitations |
| 4 | Word Embeddings | Word2Vec, GloVe, FastText, Contextual embeddings, Use cases |
| 5 | Language Models | Definition, Types (n-gram, neural), Training, Applications, Evaluation |
| 6 | Part-of-Speech Tagging | POS tags, Tagging techniques, Rule-based, Statistical, Evaluation metrics |
| 7 | Named Entity Recognition (NER) | Definition, Applications, Techniques, Libraries, Challenges |
| 8 | Syntax & Parsing | Dependency parsing, Constituency parsing, Parse trees, Applications, Tools |
| 9 | Sentiment Analysis | Polarity detection, Techniques, Lexicon-based, ML-based, Applications |
| 10 | Text Classification | Supervised learning, Feature extraction, Algorithms, Evaluation, Use cases |
| 11 | Topic Modeling | LDA, NMF, Applications, Preprocessing, Evaluation |
| 12 | Word Sense Disambiguation | Definition, Techniques, Knowledge-based, Supervised, Evaluation |
| 13 | Machine Translation | Rule-based, Statistical, Neural MT, Evaluation, Challenges |
| 14 | Question Answering Systems | Definition, Types, Techniques, Datasets, Applications |
| 15 | Speech Recognition & NLP | ASR, Pipeline, Feature extraction, Speech-to-text, Applications |
| 16 | Text Summarization | Extractive, Abstractive, Techniques, Evaluation, Tools |
| 17 | Information Retrieval | Search engines, Indexing, Ranking, Query processing, Evaluation |
| 18 | Information Extraction | Definition, Named entities, Relationships, Event extraction, Tools |
| 19 | Coreference Resolution | Definition, Techniques, Rule-based, ML-based, Applications |
| 20 | Text Generation | Language models, Techniques, GPT, Applications, Evaluation |
| 21 | Dialogue Systems & Chatbots | Rule-based, ML-based, Retrieval-based, Generative, Applications |
| 22 | Deep Learning for NLP | RNN, LSTM, GRU, Transformers, Applications |
| 23 | Transformers & BERT | Architecture, Attention mechanism, Pretrained models, Fine-tuning, Applications |
| 24 | Named Entity Linking | Definition, Knowledge bases, Techniques, Applications, Challenges |
| 25 | Text Similarity & Semantic Search | Cosine similarity, Embeddings, Semantic search, Applications, Tools |
| 26 | Evaluation Metrics in NLP | Accuracy, Precision, Recall, F1-score, BLEU, ROUGE |
| 27 | Pretrained NLP Models | GPT, BERT, RoBERTa, XLNet, Use cases |
| 28 | NLP in Industry Applications | Healthcare, Finance, E-commerce, Social media, Customer support |
| 29 | Ethics & Bias in NLP | Bias in data, Fairness, Mitigation strategies, Privacy, Regulatory compliance |
| 30 | Future Trends in NLP | Multilingual models, Large language models, Conversational AI, Explainability, Research directions |
