Courses

This course introduces essential concepts of natural language processing (NLP) with emphasis on the methods to extract actionable insights from unstructured text data. The topics include text clustering and classification, similarity analysis, text summarization and topic modeling.

After completing this course you will be able to:

• Understand the basics of natural language processing and identify the challenges and constraints of mining text data;
• Apply data preprocessing techniques to address challenges specific to text data, including structuring unstructured data, and dimensionality reduction according to linguistic context;
• Build and evaluate NLP models using supervised and unsupervised machine learning techniques specific to text mining;
• Apply state-of-the-art NLP frameworks such as NLTK, Gensim and spaCy for designing and evaluating the NLP models including sentiment analysis, text summarization and topic modeling.