CS · AI

Natural Language Processing

32 hours, 38 minutes 2 Seconds

Description

From chatbots to search engines, natural language processing powers how machines understand human language. This course covers text preprocessing, language modeling, and modern transformer-based architectures, giving students hands-on experience building NLP applications with industry-standard tools.

What Students Will Learn

+ Text Preprocessing and Tokenization ›
+ Classical NLP Techniques ›
+ Word Embeddings and Language Models ›
+ Transformer Architectures and Applications ›

Overall Learning Outcomes

  1. NLP Fundamentals: Apply core text preprocessing and feature extraction techniques.
  2. Modeling Skills: Build and evaluate language models for text-based tasks.
  3. Modern Architectures: Understand and apply transformer-based models in practical NLP problems.
  4. Applied Projects: Develop functioning NLP applications using industry-standard libraries.
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