About Bundle
The course begins with core NLP concepts such as text preprocessing, tokenization, text cleaning, POS tagging, text representations (BoW, TF-IDF), and word embeddings like Word2Vec and GloVe. Learners then move into deep learning for NLP, covering ANN basics followed by sequence models including RNNs, Bidirectional RNNs, LSTMs, and Bidirectional LSTMs.
Advanced topics such as Encoder-Decoder architectures, Attention mechanisms, and Transformers are explained in depth, along with self-attention, multi-head attention, and positional encoding. The course also includes hands-on implementation using Python, TensorFlow, and Keras, real-world business use cases, and NLP-specific evaluation metrics such as BLEU, ROUGE, and Perplexity. By the end, learners will be equipped to design, train, and evaluate modern NLP models for real-world applications.
Why Enroll in This Course?
End-to-End NLP Learning Path
Master NLP from text preprocessing to advanced Transformer architectures.
Industry-Relevant Curriculum
Covers RNNs, LSTMs, Attention, and Transformers used in real-world NLP systems.
Hands-On & Practical
Learn through Python, TensorFlow, and Keras implementations with real datasets.
Modern NLP Techniques
Build expertise in Word Embeddings, Language Modeling, and Deep Learning for NLP.
Business-Centric Use Cases
Apply NLP solutions to real-world scenarios like chatbots, text classification, and sentiment analysis.
Evaluation Metrics Covered
Learn NLP-specific metrics such as BLEU, ROUGE, Perplexity, Precision, Recall, and F1-Score.
Beginner to Advanced Progression
Structured learning path suitable for students moving from basics to advanced NLP.
Career-Ready Skills
Gain practical skills required for NLP Engineer, AI Engineer, and Data Scientist roles.