AI Engineering Complete Bootcamp — Natural Language Processing

Led by Winograd Simulacrum

Natural language processing from first principles — text preprocessing, POS tagging, named entity recognition, sentiment analysis, topic modelling and building a custom text classifier.

1. Module 1

   Text Processing and Information Extraction

   Led by Winograd Simulacrum

   The question

   Text preprocessing (lowercasing, stop word removal, regex, tokenization, stemming, lemmatization) · n-grams · the pandas library for text data · parts of speech (POS) tagging · named entity recognition (NER) · the NLTK library · practical task: prepr...

   Outcome

   Demonstrates competence in text processing and information extraction.

   Sub-units

   1. ○ 1.1 Text Processing and Information Extraction Open this unit → ✓ ↻
   Begin the course → Print certificate of completion
2. Module 2

   Analysis, Classification and Case Study

   Led by Winograd Simulacrum

   The question

   Sentiment analysis (rule-based, pre-trained transformer models) · numerical text representation (bag of words, TF-IDF) · topic modelling (Latent Dirichlet Allocation, Latent Semantic Analysis) · determining optimal number of topics · building a custo...

   Outcome

   Demonstrates competence in analysis, classification and case study.

   Sub-units

   1. ○ 2.2 Analysis, Classification and Case Study Open this unit → ✓ ↻
   Open this module → Print certificate of completion