Classic NLP Masterclass

A 20-hour NLP masterclass on the classical text-analytics stack — cleaning, TF-IDF, POS tagging, named-entity recognition, topic modeling and text classification. You leave able to turn raw, unstructured text into structured signals your models can use.

Working on real text, you clean and represent it (regex, TF-IDF), tag and extract entities, model topics, and build classifiers. The capstone is a working text-analytics pipeline.

• Analysts and data scientists working with text data.
• Teams building search, tagging or document-classification features.

• Clean, normalize and represent text data.
• Extract entities and part-of-speech information.
• Model topics across a document collection.
• Build accurate text-classification models.
• Assemble an end-to-end NLP pipeline.

• Hands-on labs throughout the program (70% project-based).
• A capstone project demonstrating end-to-end skills.

• Build text-classification and entity-extraction pipelines.
• Turn unstructured text into structured, analyzable signals.

Globally accredited certificate issued by Epsilon AI Learning — USA, with a unique Certificate ID and EPSILON ID. Awarded on 80% attendance, 80% final exam, and a capstone project.

• Cleaning and normalizing text
• Tokenization and stemming/lemmatization
• Regular expressions (regex)

• Bag-of-words and TF-IDF
• N-grams and vocabularies
• Feature extraction for models

• Part-of-speech (POS) tagging
• Named-entity recognition (NER)
• Building extraction pipelines

• Topic modeling (LDA)
• Clustering documents
• Interpreting topics

• Building classifiers
• Evaluation and imbalance
• Sentiment and intent

• Framing a text problem
• Building an end-to-end pipeline
• Turning text into structured signals