Course Outline

Day 1 – Introduction, Text Data, Preprocessing
1. Introduction to NLP
2. Collecting and Managing Text Data
3. Linguistic Basics & Text Preprocessing
4. Building a Preprocessing Pipeline
 

Day 2 – Text Representation, Classification, Clustering, Topic Modeling
1. Text Representation Techniques
2. Text Classification Methods
3. Document Clustering and Dimensionality Reduction
4. Topic Modeling and Interpreting Topics
 

Day 3 – Embeddings, Modern NLP, End-to-End Project
1. Embeddings and Advanced Text Representations
2. Practical NLP with spaCy & Hugging Face (Named Entity Recognition (NER) and Sentiment Analysis)
3. Introduction to Transformers
4. End-to-End Project Implementation

 21 Hours

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