Natural Language Processing (NLP) — ChatGPT-like models, sentiment analysis, LLMs

Categories: AI/ML, CSE
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About Course

The Natural Language Processing (NLP) course explores how machines understand and generate human language.
From text preprocessing and sentiment analysis to training and fine-tuning large language models (LLMs) like ChatGPT, this course provides an end-to-end understanding of how AI systems process language.

Students will learn to use Python, TensorFlow, and Hugging Face Transformers to build their own NLP pipelines — including text classification, chatbot creation, and prompt-based LLM applications.

By the end, you’ll have the expertise to build intelligent text-driven applications and understand the fundamentals powering today’s most advanced conversational AIs.

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What Will You Learn?

  • Understand the foundations of NLP and text data representation.
  • Perform tokenization, stemming, lemmatization, and text cleaning.
  • Build sentiment analysis and text classification systems.
  • Apply traditional models (Naive Bayes, SVM) for NLP.
  • Implement sequence models using RNNs, LSTMs, and GRUs.
  • Learn transformer architecture and attention mechanisms.
  • Use pre-trained models (BERT, GPT, T5) via Hugging Face.
  • Fine-tune ChatGPT-like models for custom NLP tasks.
  • Build and deploy chatbots and text analysis applications.

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