Natural Language Processing (NLP) with Python

Module 1: Introduction to NLP

• Basics of natural language processing.
• NLP applications and use cases.
• Text data preprocessing.

Module 2: Text Classification and Sentiment Analysis

• Text classification techniques.
• Sentiment analysis with Python.
• Building NLP pipelines.

Module 3: Named Entity Recognition (NER)

• Identifying entities in text.
• NER models and libraries (e.g., spaCy).
• Entity linking.

Module 4: Text Generation and Language Models

• Generating text with NLP models.
• Language models (e.g., GPT-3).
• Text summarization and translation.

Module 5: NLP in Action

• Building NLP applications (e.g., chatbots).
• Ethics and biases in NLP.
• Future trends in NLP.