Welcome

Hello NLP learners! Welcome to our Introduction to NLP Course. Please prepare to explore the interesting world of Natural Language Processing. Get set to dive into text preprocessing, word embeddings, traditional machine learning, and the latest NLP practices. 

This program includes video lessons, notebooks, exercises, and much more!
This 7-part course will cover the following:

  • Tokenization and Stop Word Removal
  • Stemming and Lemmatization
  • Counting-Based Embeddings
  • Neural Network-Based Embeddings
  • Classic Machine Learning in NLP
  • Deep Learning for NLP
  • Large Language Models

Our instructor, Mary Moesta, an experienced ODSC Instructor, is thrilled to guide you through this program. 


Course curriculum

  • 1

    Welcome to the course!

    • Welcome to Introduction to NLP Course

    • What You'll Learn in This Course

    • How to use this course

    • Course Prerequisites

    • Before we begin...
  • 2

    Lesson #1: Tokenization and Stop Word Removal

    • Introduction to NLP: Tokenization and Stopwords

    • Lesson Notebook - Tokenization and Stopwords
  • 3

    Lesson #2: Stemming and Lemmatization

    • Stemming and Lemmatization

    • Lesson Notebook - Stemming and Lemmatization

    • Time to Practice! - Steamming and Lemmatization
  • 4

    Lesson #3: Counting-Based Embeddings

    • Counting-Based Embeddings

    • Lesson Notebook - Counting-Based Embeddings
  • 5

    Lesson #4: Neural Network-Based Embeddings

    • Neural Network-Based Embeddings

    • Lesson Notebook - Neural Network-Based Embeddings

    • Time to Practice! Neural Network-Based Embeddings
  • 6

    Lesson #5: Classic Machine Learning in NLP

    • Classic Machine Learning in NLP

    • Lesson Notebook - Classic Machine Learning in NLP
  • 7

    Lesson #6: Deep Learning for NLP

    • Deep Learning for NLP

    • Lesson Notebook - Deep Learning for NLP

    • Time to practice! - Deep Learning for NLP
  • 8

    Lesson #7: Large Language Models

    • Large Language Models

    • Lesson Notebook - Large Language Models

  • 9

    Resources and Data Files

    • Download Your Data Files Here
  • 10

    Supplementary Lessons - Introduction to NLP

    • Entity Recognition

    • Sentiment Analysis

    • Text Scraping and Cleaning

    • Text Summarization

    • Topic Modeling

    • Translation
  • 11

    Next steps

    • Before you go...

    • Course Feedback