Description

Course Overview:
This course provides an in-depth exploration of Natural Language Processing, a key AI discipline that enables machines to understand, interpret, and generate human language. You'll work on techniques used in chatbots, sentiment analysis, and text summarization.

Course Curriculum:

• Introduction to NLP: Basics of NLP, text preprocessing, tokenization, and stemming.
• Text Representation: Bag-of-words, TF-IDF, Word2Vec, and embeddings.
• Text Classification: Sentiment analysis, spam detection, topic modeling.
• Sequence Models: Working with sequence data using RNNs and LSTMs.
• Advanced NLP Topics: Named entity recognition (NER), machine translation, and text summarization.
• Hands-on Exercises: Building NLP applications using NLTK, SpaCy, and Hugging Face.

Skills Gained:
Building NLP models, text preprocessing, working with language models, and text-based AI applications.