Natural Language Processing

Join our transformative NLP primer course for a comprehensive understanding of Natural Language Processing and its diverse applications.

This course covers NLP fundamentals, essential tools, regex mastery for text pattern recognition, and in-depth text analysis. Learn to extract insights from text data with word, sentence, and n-gram analysis. Delve into vectorization, including cosine distance and TF-IDF. Explore semantic analysis through eigenvalues, eigenvectors, and LSA. Master document classification with Naïve Bayes, word embeddings, deep learning, and cloud services. Elevate your NLP expertise and open doors to countless opportunities in this field. Join us today for an exciting journey into NLP!

Dr. Ash Pahwa
Instructor, Caltech CTME

In this course, you will learn to:

  • Gain a comprehensive understanding of the pervasive nature of Natural Language Processing (NLP) applications

  • Explore the practical use of software tools such as NLTK and TextBlob to extract and comprehend the meaning within textual data

  • Delve into the intricacies of Word Embeddings and Transformers, vital components employed by search engines to decipher the semantics and context of text

This is a four-hour, non-technical overview of key topics and their application in a business environment for the purpose of building familiarity and early subject literacy. Combine this course with others to comprehensively understand broad technological change affecting most industries. Each chapter takes about 20 minutes and ends with a two-question learning check focusing on topic recall and retention.

This short course is ideal for most business function personnel across the enterprise, including products and services, accounting, sales and marketing, operations, and supporting roles.

  • Basics
  • Welcome!
  • Introduction
  • Course Outline
  • Summary Deck
  • Chapter 1: NLP and its Applications
  • NLP and its Applications
  • Chapter 1: Knowledge Check
  • Article
  • Chapter 2: History and Tools for Processing Natural Language
  • History and Tools for Processing Natural Language
  • Chapter 2: Knowledge Check
  • Article
  • Chapter 3: Regular Expressions Basic Text Processing
  • Regular Expressions Basic Text Processing
  • Chapter 3: Knowledge Check
  • Article
  • Chapter 4: Text Analysis
  • Text Analysis
  • Chapter 4: Knowledge Check
  • Article
  • Chapter 5: Vectorization
  • Vectorization
  • Chapter 5: Knowledge Check
  • Article
  • Chapter 6: Semantic Analysis / Latent Semantic Analysis
  • Semantic Analysis / Latent Semantic Analysis
  • Chapter 6: Knowledge Check
  • Article
  • Chapter 7: Text Classification Using Machine Learning Tools
  • Text Classification Using Machine Learning Tools
  • Chapter 7: Knowledge Check
  • Article
  • Chapter 8: Deep Learning + Word Embeddings
  • Deep Learning + Word Embeddings
  • Chapter 8: Knowledge Check
  • Article
  • Chapter 9:
  • Cloud Services for NLP
  • Chapter 9: Knowledge Check
  • Article
  • Course Completion
  • Final Quiz
  • Course Feedback
Completion rules
  • All units must be completed