Explore sequence-based neural networks including RNN, Bidirectional RNN, LSTM, and Bidirectional LSTM with hands-on Python implementation. Learn Encoder-Decoder and Attention mechanisms, followed by an in-depth study of Transformer architecture, self-attention, and decoder blocks. The course also covers essential NLP evaluation metrics such as BLEU, ROUGE, and Perplexity for model assessment.