Text Analytics and NLP Data Preparation

Natural Language Processing (NLP) relies heavily on the quality of textual data. This program focuses on preprocessing and preparing text data for analytics and machine learning. Participants will learn advanced text-cleaning techniques, vectorization, feature extraction, and dimensionality reduction to convert unstructured text into actionable insights.

The course emphasizes hands-on exercises and real-world applications such as sentiment analysis, document classification, and topic modeling. Participants will be able to process complex text datasets and integrate them into analytics or predictive models.

• Preprocess and clean large volumes of text data.
• Apply text vectorization and embedding techniques for modeling.
• Reduce dimensionality of textual features for efficient computation.
• Extract features suitable for sentiment analysis, clustering, or classification.
• Integrate NLP-preprocessed data into analytical pipelines.