This session covered the foundational principles of Natural Language Processing, focusing on how machines interpret, analyze, and generate human language. Participants learned key NLP concepts such as tokenization, stemming, lemmatization, sentiment analysis, and text classification.

The workshop included interactive Python exercises using libraries like NLTK and spaCy, as well as discussions on real-world applications of NLP in AI systems such as chatbots and language models.

By the end of the training, attendees gained a practical understanding of text preprocessing and basic model development for natural language tasks.