Natural Language Processing
Whether you’re a novice or an experienced professional, our curated Machine Learning courses cater to diverse skill levels, providing a comprehensive and hands-on learning experience.
Skills You Will Gain
Data Cleaning
NLTK
Spacy
RNN
LSTM
GRU
Transformer
ChatGPT
This course includes
- 1 : 1 Session
- 100% Placement Assistance
- 15 Weeks + Projects
- Real TIme Project Training
Syllabus Overview
- – What is NLP?
– Applications of NLP
– Tokenization, Stopword Removal, Stemming, and Lemmatization
- – Bag of Words (BoW), TF-IDF
– Word Embeddings (Word2Vec, GloVe)
– N-grams, Markov Models, Hidden Markov Models (HMMs)
- – Role of POS tagging in NLP
– POS tagging algorithms
– Introduction to NER
– Rule-based and machine learning-based NER systems
- – Understanding sentiment analysis
– Sentiment analysis techniques
– Supervised text classification
– Building text classifiers using different algorithms
- – Introduction to sequence-to-sequence models
– Applications of Seq2Seq models
– Attention mechanisms in NLP applications
– Deep dive into the Transformer architecture
– Pre-trained Transformers (e.g., BERT, GPT)
– Fine-tuning pre-trained Transformers for NLP tasks
- – Introduction to text generation
– Recurrent Neural Networks (RNNs) for text generation
– Generating text with RNNs and LSTM
– In-depth exploration of GPT-3
- – Advanced text classification techniques
– Building custom NER models
– Evaluation metrics for NER
– Introduction to Automatic Speech Recognition (ASR)
– Text-to-Speech (TTS) synthesis
– Integrating ASR and TTS into NLP applications
– Ethical considerations in NLP (bias, privacy)
– Recent developments and future trends in NLP
– Student presentations on NLP projects or research
Transform Your Skills: Enroll Now to Learn AI
This condensed roadmap still covers essential NLP concepts and techniques while being more organized in a 10-week format. You can adjust the pace and depth of each topic based on the needs of your course and students.